Computational Biology (Fall 2024)

Course number: BIOSC 1540
Semester: Fall 2024
Website: pitt-biosc1540-2024f.oasci.org
Meeting time: Tuesdays and Thursdays 4:00 PM - 5:15 PM
Location: 1501 Posvar

Grade distribution

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Below is the final grade distribution of the 72 students in the class and some key takeaways:

• The vast majority of students (88.9%) demonstrated proficient understanding of the material;
• Students with a C- or lower in the course attended only 16% of the classes (excluding exam days);
• Out of the 30 students who received an A- or above, 8 of them (26.7%) were not computational biology majors.

A+ (8.3%)

A (16.7%)

A- (16.7%)

B+ (11.1%)

B (5.6%)

B- (13.9%)

C+ (6.9%)

C (9.7%)

C- (2.8%)

D+ (0.0%)

D (1.4%)

D- (2.8%)

F (4.2%)

Teaching evaluations

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The following passages are unmodified student responses (58 out of 72) to a Course Survey administered by OMET.

The standards the instructor set for me were

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Too low: 0

Appropriate: 40

Too high: 18

How many hours per week did you usually spend working on this course outside of classroom time?

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Less than one hour: 0

One to three hours: 16

Four to six hours: 37

Seven to nine hours: 5

Ten or more hours: 0

The instructor created an atmosphere that kept me engaged in course content

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Strongly disagree: 1

Disagree: 4

Neutral: 9

Agree: 26

Strongly agree: 18

The instructor was prepared for class

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Strongly disagree: 0

Disagree: 3

Neutral: 3

Agree: 31

Strongly agree: 21

The instructor treated students with respect

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Strongly disagree: 0

Disagree: 1

Neutral: 2

Agree: 18

Strongly agree: 37

The instructor was available to me (in-person, electronically, or both)

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Strongly disagree: 0

Disagree: 1

Neutral: 8

Agree: 19

Strongly agree: 26

N/A: 4

The instructor evaluated my work fairly

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Strongly disagree: 1

Disagree: 5

Neutral: 12

Agree: 19

Strongly agree: 19

N/A: 2

The instructor provided feedback that was helpful to me

#

Strongly disagree: 2

Disagree: 2

Neutral: 9

Agree: 20

Strongly agree: 22

N/A: 3

I learned a lot from this course

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Strongly disagree: 0

Disagree: 2

Neutral: 6

Agree: 21

Strongly agree: 29

The instructor creates an inclusive learning environment for all students

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Strongly disagree: 0

Disagree: 2

Neutral: 4

Agree: 18

Strongly agree: 34

The course was intellectually challenging

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Strongly disagree: 0

Disagree: 0

Neutral: 3

Agree: 27

Strongly agree: 27

I could ask a question or make a comment if I wanted to

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Strongly disagree: 1

Disagree: 0

Neutral: 3

Agree: 25

Strongly agree: 28

This course helped to develop my ability to solve real problems in this field

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Strongly disagree: 1

Disagree: 4

Neutral: 5

Agree: 28

Strongly agree: 19

This course helped to broaden my interests

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Strongly disagree: 0

Disagree: 5

Neutral: 7

Agree: 22

Strongly agree: 23

Not requiring Python has positively impacted my learning experience in this course

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Strongly disagree: 7

Disagree: 13

Neutral: 17

Agree: 7

Strongly agree: 11

Incorporating required programming assignments would enhance my understanding of course material

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Strongly disagree: 1

Disagree: 5

Neutral: 14

Agree: 22

Strongly agree: 14

I feel more confident about pursuing a career in computational biology after taking this course (if desired)

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Strongly disagree: 3

Disagree: 6

Neutral: 12

Agree: 24

Strongly agree: 11

The skills learned in this course are relevant to my career goals

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Strongly disagree: 0

Disagree: 2

Neutral: 11

Agree: 20

Strongly agree: 23

This course should be split into computational biology major and non-major sections

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Strongly disagree: 0

Disagree: 4

Neutral: 14

Agree: 19

Strongly agree: 19

The computational biology major curriculum effectively integrates biological concepts with computational methods

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Strongly disagree: 2

Disagree: 10

Neutral: 9

Agree: 18

Strongly agree: 17

The computational and biological components of the computational biology major are well integrated

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Strongly disagree: 1

Disagree: 12

Neutral: 11

Agree: 20

Strongly agree: 12

Courses for the computational biology major include an appropriate amount of practical applications

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Strongly disagree: 2

Disagree: 12

Neutral: 17

Agree: 18

Strongly agree: 7

The career planning guidance available for computational biology students at Pitt meets my needs

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Strongly disagree: 6

Disagree: 13

Neutral: 22

Agree: 10

Strongly agree: 5

Research opportunities in computational biology at Pitt are readily available to students

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Strongly disagree: 4

Disagree: 10

Neutral: 19

Agree: 18

Strongly agree: 5

Industry connections are readily available to computational biology students

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Strongly disagree: 5

Disagree: 14

Neutral: 29

Agree: 8

Strongly agree: 0

What did you like best about how the course was taught?

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• The lecture slides, the method the material was taught, and the assignments.

• I liked the content that we learned in this class. It was interesting and engaging. I also liked that we were able to have hands on practice with different tools.

• I liked how the coding aspects were separate from the class content.

• The problem sets were a good way to gauge our understanding of the past 2 or more lectures and really delve into our basic understanding of the content.

• I liked that we learned about current bioinformatics softwares.

• You’re a really nice instructor and provided entertaining lectures! I also enjoyed the layout of the grading and the bonus for assignments turned in on time, and definitely appreciated the cheat sheets for exams. The articles about each topic was a really good idea too.

• I liked the structure of the lecture slides and how he had a lot of materials posted to the course website.

• I liked that all lecture notes were available online.

• I liked how knowledgable Dr. Maldonado was. He not only taught us well but would drop knowledge on us that inspired me to want to really learn more about the course.

• I liked that presentations had the little follow online link and a lot of topics were interesting and thoroughly discussed (or boring but extremely necessary in this major, so I had to suffer and learn).

• I liked how things were taught in class, I thought a lot of the more complicated concepts were explained well.

• Multiple aspects on Computational Biology, which is helpful for us to learn the full area of CompBio.

• I liked how the homework questions were at the end of the semester, because I feel they were tailored to help learn the content.

• I liked how Alex structured the lecture slides into subtopics and really made sure we knew the info before moving on. It is clear that Alex knows a lot and also cares a lot about his students. He teaches with enthusiasm and helps us outside of class and office hours if needed.

• I like how the weekly assignments encourage us to learn and memorize what we have learnt on time.

• Open source / accessible; different medium than canvas; openness to feedback; responsive to emails and enough office hours; no false conceptual frameworks; challenging questions.

• I thought that the material was interesting, and I liked how student feedback was taken into account and adjustments were made when needed. The grading distribution seems okay. The professor is nice and he seems like he actually cares about the students.

• The expectations were clear and the coursework was consistent with the material taught. I also liked the testing format.

• Computational structural biology.

• Instructor created very thoughtful slides and graphics that helped make concepts easier to understand. Instructor also created engaging lectures and provided a lot of additional resources for understanding subject matter.

• I thought that Dr. Maldonado was really good at keeping things down–to–earth, and did a good job of making connections between more difficult concepts and real–world examples/well–known examples that helped me understand things more.

• I thought the lectures did a good job with deep dives into specific computational biology “ideas”, such as with BWT or classical approximations for MD sims. I thought it gave a very good idea for how they worked, while maintaining the right depth considering the pre–reqs for the course. I also enjoyed how the course covered so many varied topics that combined a large number of other classes I have taken (or will take) together. I just found it fun when I could talk about stat mech with friends in modern physics because of a comp bio course I took.

• I liked how the learning objectives were outlined for every lecture, which helped guide my studying.

• I liked the lecture style and how we could follow along with the slides on our own computers. I also liked how questions could be asked over TopHat anonymously.

• I liked the slides and when they were available I especially liked the other sources he would include in the section about the lecture we just did.

• I appreciated the way he tried to break down different difficult concepts. I do think there was a better way to kind of tie in the computational aspect of things, or at least the use of different packages and databases, that wasn’t directly related to programming.

• The slides were will done so that all the information was on it in way that wasn’t overwhelming. Also the lecture was done in a way that was both informative and not–boring.

• I liked the bonus for turning stuff in on time; I also liked the website with the information. It was much easier to navigate and have lots of information on compared to canvas. I liked the grading scale as well. It made it so that one bad exam wouldn’t bomb your grade. Grading projects, tests, and assignments are basically the same weight allowed students to diversify their skills.

• I liked that this course was challenging and made us work for the grades. Dr. Maldonado is also very helpful and encouraging to students and incorporates new developments in the field into the course. I also appreciate how there were multiple opportunities to increase the grade, as this course is very difficult for someone first learning about these topics.

• The slides that you provided and your website were set up really nicely. I appreciated all of the resources you provided. The HW though took much time, really helped me understand the concepts better.

• Professor made the course so that everything we learned would apply to how we would use information in workplace.

• Alex’s class is incredibly engaging, and he has a knack for simplifying complex concepts. Attending his office hours is highly recommended. The class introduces both bioinformatics and computational biology criteria, providing me with a comprehensive understanding of each. This knowledge helps me identify which criteria resonate with me the most and aligns with my future goals. The class introduces many novel concepts that I believe are very useful for my future work. It solidifies my passion for computational biology, and I had a lot of fun.

• The slides are helpful, but that is it.

• Even though a lot of the concepts seem to be a lot more complicated, Dr. Maldonado did a great job of explaining the content and going into more detail or using analogies to help explain some of these. He was also very accessible, and office hours were extremely helpful. I also like how there was background reading for the lectures just to help understand the content better.

• N/A

• The lectures were interesting and engaging, but I would have liked them beforehand to prepare for the lecture.

• I liked the “flipped” classroom approach when that was a thing. I find it extremely helpful to prime to my brain before anything and it was especially helpful for complex topics this course introduces. I also think the grading system is pretty lenient. I liked all the theory it introduces as well, I feel like I learned a lot about the field and who the big players are in it, alongside what they’re doing and what they’re using to accomplish their advancements. I thought the review guides for the exam were also extremely helpful and effectively guided my preparation. I also appreciated that demonstration of tools during lecture. I’m also excited to do the final project, it seems extremely interesting and educational.

• Very organized.

• I liked the simulation part of the course.

• Office hour available.

• I like how the hw was based on concepts in class.

• I liked how the homework helped me understand the course material even if it wasn’t so clear after lecture.

• What I liked best about this course is it allowed me to understand computational biology and what it truly is as a field since it was something I was interested in. Coming into the course I knew it would be challenging and I can say that the instructor explained the concepts in a way that made sense. I could comprehend coming from a field of limited knowledge of algorithms and other computer science–based aspects of the course.

• I didn’t like much about how the course was taught by this professor. It was hard to retain concepts, and there were no supplemental material to turn to if you were having trouble. This was a problem since the slides were so bare–bones.

• The material was interesting and Dr. Maldonado clearly had a deep understanding of the material.

• I liked that there were opportunities to utilize computational tools.

• I like that the lectures built off of one another, and that the PDFs were made available immediately following the lecture. There was always time to ask questions, and the content was straight forward.

• i liked the exam format and homeworks

• The way Alex teaches this course is fun and engaging. For the first time in all four years of my Biology career at Pitt I felt excited to come to class and learn new material. A good teacher really does make all the difference.

• I enjoyed the lecture portion of the course and found Dr. Maldonado to be very informative.

• Taught based on what we felt we needed more or less help with.

• I honestly enjoyed how the tests were formatted. By changing the points to be aligned with question difficulty, it made it less pressure while still making sure we understood the content.

• Dr. Maldonado masterfully made complex concepts easy to digest. His personable and approachable attitude made coming to class a delight rather than a slog, and combined with a lecturing style employing active student participation, visualizations, and comparisons to concepts we understand outside of class (like comparing micro state–based entropy to a coordinate system with points), made understanding difficult material much easier.

  Dr. Maldonado consistently exposed us to the bigger picture, discussing how class concepts were used in labs around Pitt (also encouraging students to get into research!) and where the field may go in the future. This kept me engaged with the content, making it feel far more tangible, and by discussing real–would applications, improved my understanding of class concepts.

  Additionally, Dr. Maldonado gave outside–of–class opportunities for students wanting to practice more coding–related skills relevant to computational biology — this increased accessibility and engagement across the various student demographics in the class (majors who may he experienced in programming, and non–majors wanting to learn about a new field).

  He gave a comprehensive view of computational biology, leaving me feeling genuinely prepared to pursue computational biology research and excel in future major courses.

• I liked how friendly and personable the professor was with the students. He was very approachable during class and office hours and tried his best to make the course manageable despite the heavy amount of lecture content.

If you were teaching this course, what would you do differently?

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• I would make the first portion of the assignment available in the first half of the semester.

• I wish the content was split differently so that exams had less content. If there was a quiz–based approach I think it would be easier to do better in the course. Also, I wish we did more Python for the people who are taking this class for their major.

• I would not do anything differently.

• I feel like the way the information is presented straight from lecture without prior reading content makes it difficult to understand in one sitting during lecture and I’m not able to fully focus when so much information that I’ve never seen before is getting thrown at me.

• I would include some more R and Python that would count as extra credit and would have fewer questions on the homework assignments since they were hard to finish and keep up with.

• I understand why you would keep the PDFs of the slides unavailable until after the lecture, but I found it tough to take notes effectively this way. Usually if I have a PDF of the slideshow already with me I only need to write down what the instructor says (which for this class, is a lot of important info) on top of the existing slides, but here I ended up juggling between trying to write down info from the slides, taking screenshots before I missed them (since I couldn’t go back on the slides myself), and trying to remember what was being spoken. Of course this is just personal preference, but I feel like it would be much easier and better for retaining information from lecture if we were provided the slide PDFs before/during lecture.

• I understand why you would keep the PDFs of the slides unavailable until after the lecture, but I found it tough to take notes effectively this way. Usually if I have a PDF of the slideshow already with me I only need to write down what the instructor says (which for this class, is a lot of important info) on top of the existing slides, but here I ended up juggling between trying to write down info from the slides, taking screenshots before I missed them (since I couldn’t go back on the slides myself), and trying to remember what was being spoken. Of course this is just personal preference, but I feel like it would be much easier and better for retaining information from lecture if we were provided the slide PDFs before/during lecture.

  The exams could be a bit rough and I also felt like some of the homework was hard to answer without substantially googling or looking up the answers and sometimes it seemed to go much more in depth than the lectures. However I also understand that there’s a lot of high level content to try to pack into this class and that’s probably difficult.

  The final project though was way beyond the scope of what we were taught in class and there were little to no resources about it online or posted on the website. Part 1 was perfectly fine, but Part 2 and 3 were incredibly tough due to lack of knowledge on the programs and files we used and with not enough guidance (there was a lot of guidance for Part 1 but suddenly very little for Part 2 and 3 which were the more complex parts), and that the questions asked (especially on Part 2 and 3) also involved way more depth and information than what we had actually learned in this course. I found myself clueless on many questions and struggling a lot on the final project!

  I think overall I just wish the expectations of the course wasn’t set so high especially since this course is so broad in topics, and I wish we had more guidance on assignments/projects/exams.

• I would provide more practice problems with answer keys that are similar to the exams because the exams were pretty difficult and it was hard to know what to study for it.

• Maybe I would introduce some discussion board assignments? Since some questions have more than one answer, it may help to hear every students’ opinions.

• Some things that were really hard to understand were brushed over sometimes, but we should’ve just asked more questions because he always asked for input and if we needed to go over something again.

• I was really sad that we did no programming in relation to compbio – additional assignments are good, but with no grades/extra credit it’s hard to find time to spend several hours doing them, I always ended up prioritizing rest/learning something else, new and more fun. Also, some lectures were rushed bcs we spent 40 minutes discussing the easiest thing possible and then had 5 minutes for each slide with ton of difficult information. A lot of HW questions were not based on readings/slides, but somehow we were expected to know the answers.

• I would better specify what we need to know for homeworks/exams during the notes because certain topics we talked about in class but didn’t need to know too much for the homeworks/exams and vice versa.

• I would put less detail and focus on the most basic concepts. Also, I would make my slides a clearer structure (Eg. with a mind map).

• Each test had so much material on it, it was hard to comprehend and apply everything for so much material. I would’ve rather had more tests that covered less material each that the big midterms we did have.

• I would make the exams less multiple choice based and more open ended based as some of the concepts are better tested with written responses than picking the best option.

• I would make adjustments to exams so the answer choices were not too tricky. It’d be better if they are mostly straightforward instead of having hard reading sentences.

• I already gave everything I would have done differently as direct feedback over email, which was integrated into the lectures already. It just included some ideas I had to reduce cognitive load by contextualizing material.

• Post lecture slides and relevant content a little earlier than during/after lecture. I would also include practice problems since the test question wording gave me a really difficult time despite knowing the concepts. More frequent TopHat questions would be beneficial. I would try to have more outside resources for some of the concepts; oftentimes I did not know where to look or even know what to search for some of the concepts taught in class. I felt the homework was graded a little bit too harshly but idk.

• I would go over the material before class to make sure there were no mistakes.

• Include coding, i learn better with practical methods, in this case coding. I understand that people choose this class as an elective but when they chose a class that has “computational” in its name, they should expect to use computers, without coding i thought it was a lot of content dumping

• I would structure the class somewhat differently. Instead of the traditional question–and–answer homework assignments, I would assign projects similar to the final project but smaller in scope. In place of the two midterm tests, I would implement biweekly quizzes that focus on the subject matter introduced in the preceding smaller projects. It might also be fun if the final project built upon these smaller projects, and allowed students some creativity, such as choosing from a selection of topics for the final project—for example, antibiotic design versus cancer drug discovery.

  For the computational biology portion of the class, I would include projects that incorporate physics–based problem solving. For instance, a homework project could involve calculating the Gibbs free energy for a protein–ligand binding interaction. Some of the course material might be easier to understand if students could engage with it in a more hands–on way.

• I would include programming officially; there were several moments where I would’ve wanted to be able to implement code to try out my understanding, and although there were extra programming questions given, I didn’t always have time to work on them due to the other work I had for the class.

• I think that there was a bit too much breadth at times, where we would cover a topic for one slide, then be expected to be masters on it. I think it would be better to spend more time on a couple topics and be expected to fully understand them, or at least for the topics that are covered more quickly, be tested less heavily on them.

• I would post the lecture slides ahead of class. Because the lecture slides were never posted before class, I found myself focusing more on copying the information from the slide than what was being said in the lecture. Also, I would be much more clear in what I expect from students in the graded assignments. The questions in our assignments were often extremely vague in terms of the professor’s expectations for our responses, and I felt they were graded unfairly.

• I would probably do a little more focus on basic concepts that are important to each unit to make sure there is a fundamental understanding. I felt like we were a little rushed sometimes.

• Have articles for every topic some of them didn’t have any articles to explain the topics and the slides rarely were hard to interpret or get full information from.

• I would record lectures and post them online. Even though I was present in class all the time, certain concepts were harder to interpret just by looking back at slides alone; having the recorded lectures to refer to and refresh my understanding of concepts would have been far more helpful for me. I think with such a lecture and content–heavy lecture, it was also hard to stay engaged 100% of the time, so being able to have the video lecture available as a buffer would have been very helpful.

  ALSO WOULD HAVE TAUGHT PYTHON!!!!! I absolutely understand the reason why you chose to take it out this semester, but now that you are thinking about bringing it back next semester, I can’t help but feel a little jipped in terms of what I could have learned throughout this course. I think that certain concepts would have been more understandable if they were taught through the more technical lens (i.e. actually using these databases instead of just talking about them).

  I think that homework assignments should have been more project–related, using things like PyMOL and SWISS–MODEL, so that the first time we would be exposed to these things would not just be in the project. It felt a little weird to be using these things for the first time in this project even though it should have been a reasonable culmination of what we had been learning. There was just a real lack of use of these different databases and platforms, outside of just programming, which I think was a major missed opportunity and learning experience. I think it would have been more beneficial to integrate it into our assignments, and it would have been more helpful to our understandings as well. Short answer assignments just did not really resonate with me; it never felt like there was a clear rubric, and the level of depth that we were supposed to go into was never really clear to me.

• Slow down the content rate, towards the end, it was hard to understand the materials. Also dial back the questions amount or deepness on the homework. With multiple homeworks and plenty of tests, I had to choose between getting a homework done on time or understanding the materials.

• I thought that the slides were vague sometimes. I appreciated the cool pictures, but sometimes it was easier to understand when Alex drew a simpler version on the white board.

• I feel like the assignments took so long due to the open nature of them. I feel to shorten them, maybe the assignments can be half multiple choice and half short answer. Students who get any multiple choice question wrong should have an option to request a regrade with the correct explanation of why their choice was wrong. If this is not an option, maybe the questions could be more focused and guided so students do not worry as much about what the “right” answer is. Also, because the lecture slides do not contain a lot of text for some questions, they are difficult to answer without doing more research.

  I also feel that the exams also had confusing wording sometimes and there were so many questions, especially for the first exam, which had to be answered before the time limit. This is a challenging course, so students should be challenged, but some of the questions felt tricky to answer due to the options and wordings of the options.

  Lastly, for lectures, I think often the lectures goes too in depth too quickly. I think the lectures can more effectively get across to students by starting with a super simple explanation anyone would be able to understand, along with the explicit goal of said experimentation or methodology. After that, it would be fine to go more in depth and explain how everything is connected. The way lectures are now, the students have to figure out a lot of the connections and learning goals by themselves, which could slow down learning in an already difficult field. For a different field, this might be more effective, but I believe the uncertainty in some of the lectures should not be left up to students in a difficult course like computational biology where a breadth of knowledge is needed.

• As a comp bio major, I think teaching a little bit more python would be nice, but I totally understand the reason for why you did not. I think the way you have it set up right now is a fair balance.

• Include python.

• I believe it would be beneficial to include video recording and taking attendance, and counting them as 5% of the total grade. While Alex is entertaining and an expert at simplifying concepts, the concept is new to us, so we still need time to process it at home. Therefore, I think watching the recording would be incredibly helpful in aiding our comprehension of the content. In fact, watching the recording would be more beneficial than reviewing the notes we take during class.

• I would engage students by providing more course material for practice and learning. The course is taught purely by looking at slides and the instructor does not put content online after class to review and help to understand. I would make sure students know what we are learning in class and have the proper prerequisites for it. This class material is relatively new in a changing field and very hard to understand, and the instructor does not help with it.

• I think that python should definitely be included in this course for later semesters since the concepts are super important, but I wouldn’t really know how to start with the code otherwise. I know there are a lot of concepts to get through, but I would have liked if maybe some less important material was taken out or taught less as I did feel like sometimes the course was extremely fast–paced, especially for something that is mostly new to me.

• N/A

• I would like more python throughout the year

• I’d give assignments back out more quickly, I didn’t have a chance to really improve my results and answers since I didn’t exactly know how I was doing, it was just a bit of a black box. I would also provide more content to prep on before lectures throughout the term because of how helpful they were to me. I would also want to implement Python into the course and to give the BIOSC classes the responsibility of applying Python for students since the CS classes teach Java, at that point it would just be a better of making sure students get practice in Python since the logic carries over between the programming languages besides a couple small changes here and there that could be knocked out as a hw assignment or during a weekend. I think I’d also provide a slight cushion to grades with something such as 5% attendance grade since you needed to be present anyway. I think more interactive questions through tophat would also be fun to introduce to get people thinking and answering questions and seeing what people can and can’t answer as it would be helpful to teach and guide self study.

• Nothing

• Give more practice tests

• I will improve my Powerpoint to make them organized. Also I would make exam prompt properly to cover the real content in the exam. It is important to set up reference book or website to fully illustrate the knowledge covered in lec.

• We had a final project and a lot was real world based and I wish that he gave us more information how to do that. I would also rather have more smaller tests rather than 2 huge tests.

• I would implement more lectures about the platforms that we needed for the final project throughout the semester because it was hard to start the final project without any background on how to use PyMol and MolModa. Additionally, I felt that the exams were very particular and the multiple choice options were so similar that I would often miss a lot of points based on a couple incorrect words in each option which I don’t think is the best way to test our understanding of the material.

• Something that I would do differently is instead of taking out Python completely from the course be a sub–part of each lecture since attending these optional Python lectures has given me insight into how to create an expression graph or heat map by coding rather than using something like excel which I think is going to be very beneficial since it gives more diverse skills that I can use in my future career when I’m working in the industry.

• I would offer more opportunities to get points that boosted our grade. Everything in the class was graded for accuracy, including homework. Homework was also far too extensive and graded far too harshly, especially for the time we were given to complete it. It would take me about 30 minutes to an hour to complete one question and homework would be about 15–20 problems long, with each question having about 3 parts.

• The slides were kind of bare and difficult to interpret. I would include more in depth resources that have clear explanations rather than vague slides.

• The questions in homework often felt like they were not able to be answered using the lecture slides and from notes taken in class. Finding information to answer the questions was time consuming. I think questions should be answerable using just information from class.

• I would probably spend more time on the matrices and string productions, as I personally found this confusing. It also seemed like this was new to others in the class as well, so I think it would be worth it to go more in depth with this content.

• try to make a little more engaging

• try to make a little more engaging

• I know the class is fairly new so its still a work in progress but just make sure there’s enough time for all the material to be presented in one lecture as well as taking time for questions into account. I also really liked when we did topcoat questions as practice, so maybe more of those.

• Maybe incorporate some basic coding back into the course.

• Include more python.

• At some points it felt we needed a background in certain subjects. I have a background in biology but not computer science and only a moderate background in physics. This left me to miss some of the background that Alex expected us to already know. I also would change the format of the site. I would put everything on canvas as that is where all other classes are located and it makes it easier for me to access.

• Bring Python back into the curriculum. And change the homework from being free–response to programming exercises. I learned how to write out algorithms very well, but I don’t know how to actually encode them, and I fear in the real–world a boss is not going to ask me to draw out Needleman–Wunsch…

• Genuinely, nothing. This has been one of the most enjoyable classes of my time at Pitt, and while difficult at times, kept me consistently engaged, putting in effort, and enjoying the course material.

• I would definitely make coding a larger part of this course, since it is expected of Computational Biology majors in their careers very often. It would be great if the coding exercises for Python that we had were extra credit. I also think a large portion of the course involves memorization of information and would have liked more problem solving, specifically with some kinds of math. Another idea – since the lectures are very heavy on content, it seemed like the professor struggled covering it in the class time and I often felt like the slides were rushed through and hard to follow. I think what I would do differently is give students some reading and exercises to do before class. Lastly, some smaller quizzes to test and keep up with material, knowing where students stand.

What aspects of the computational biology degree/program could be improved to prepare students for their careers?

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• A greater investment/expansion into the program, as more students are choosing the major. Career opportunities/advice, or mentoring.

• More major specific classes and real world applications

• I feel as though the current degree/program sets students up to be a computer scientist with a strong understanding of biological sciences, not necessary to be a computational biologist. The degree could also benefit from possible sub–fields of study(e.g. Genomics, Simulation and Modeling, etc) that allow students to take more classes that align better with their interests, instead of taking just one extra class.

• I feel like more technical skills early one will allow us to develop these critical skills early and be able to work on projects quickly.

• I think that there should be less emphasis on java and even organic chemistry. As someone that is a computational biology major that is not going to med school or applying to be a software developer, these courses take up time that I could spend learning Python or learning relevant bioinformatic research.

• More specific classes would be great.

• Make the computational biology class the same across all sections because my friend who took it a couple semesters ago said it was way different than the course I am taking right now.

• Perhaps having a better understanding of the industry component would help a lot better, as it stands for now this course is really pushing people to get higher education for a lot of job opportunities.

• no comment

• A lot of compbio labs

• I think more practical applications could be incorporated into the courses

• More class diving into specific area of CompBio.

• More research, internship, and shadowing opportunities.

• There could be more resources as well as more classes.

• Incorporating cs and biology skills can broaden students’ career options.

• N/A.

• I would like some more information and guidance on what I could do with the degree after graduation, as well as available industry connections. I also wish that the computational biology courses were offered more often and at more than one time, since having some courses offered so rarely (like BIOSC1544/1542 only being offered in alternating Spring semesters) makes it very difficult to plan my schedules. More resources for help (tutoring, etc.) with computational biology concept understanding would be really helpful.

• There aren’t many major–specific internship opportunities or hands–on classes available through the Pitt programs. A lab course might be useful.

• Class for majors and non–majors is a good idea.

• More specialized electives would be helpful. It might also be helpful if BIOSC1540 included a lab component.

• There are no high–level Python courses outside of CS0011, which is very rudimentary. I am a junior, and I won’t be taking a programming–included computational biology course until next semester. The biology–based courses don’t touch on the computational side at all, and the computing–based courses don’t touch on the biological aspects, as they’re focused on the software engineering industry standards. Additionally, it often feels that the advising staff don’t fully understand what the program looks like after school, and they seem less confident in giving advice.

• More computational biology classes, rather then a lot of comp sci and bio classes. Also having more options for classes in the major may be nice allowing for specific concentrations since the field is so broad. For instance, a more software design heavy option where you go into JS / software, or a more bio heavier focus, where you take classes like systems bio / genomics. The ideal would be if these classes could be comp bio specific, instead of being just the general versions too.

• I like how the biology department at Pitt sends out emails with updates and information, and I think it would be nice if there was something similar for Computational Biology since it is a more niche major. I feel like there’s not a lot of information being shared.

• a recitation

• I think that there should be two “optional pathways” within the computational biology degree. Like I think there should be a more data science, bioinformatics pathway and a structural biology pathway. i.e. the bioinformatics pathway would include suggested courses like Data Science with Python, Data analysis (INFSCI 0510), computational genomics, things related to the programming–heavy side of things. the structural biology pathway would include things like biophysics, that chemistry computational drug discovery course. It just feels like right now I am not really prepared for either of these fields based on the way this major is structured. Like I only know things about regression and machine learning concepts because I am a stats minor, it has nothing to do wiht actually being a computational biology major even though that is a necessary understanding and skill for this field. Like even if i wanted to learn more about structural biology, physics is a really important part of that but its not even an actual major requirement. It feels like all the prerequisites that I have taken to get to this point are really not even that relevant to this major and I waste a lot of money and time taking classes and learning concepts that I will never use again.

  The optional pathway idea is just based off of how the information sciences minor in the SCI department is structured (https://www.dins.pitt.edu/academics/minor–information–science) but I feel like it is really great for tackling and getting a better idea of skills that you need within this field. even planning wise I would have been a lot more prepared if the major was laid out for me in that viewpoint.

• Having a research capstone class, whether in simulation or genomics. This allows for people in the Comp Bio program to understand what they’re getting into.

• more python courses and more comp bio specific classes; definitely feels a little bit like I am getting 2 separate degrees in biology and computer sciences as there are not a lot of classes offered the combine the two fields.

• I do not think there is much outside of the classwork present to prepare for a career in industry. I know research is widely available, but in general, I feel that other major programs have much more resources to get internships and such that will directly help me get a job after graduation.

• .

• Provide more detailed information about the day–to–day life of working in this field, and focus on teaching marketable skills rather than just imparting basic knowledge.

• There should be more courses specifically catered to computational biology majors, and there should be less prerequisites to declare this major. The five requirements are hard to fit in quickly with all other requirements we have to do, especially if we want to pursue more academic plans.

• I wish the program relied more on coding related to python. It is nice to have the coding classes where you learn the logic, but with most of them being taught in java, I don’t feel that it would be quite as beneficial as something taught using python. If this is also a degree that is meant to prepare students for a career in comp bio, I feel that it should be stressed as an undergrad program that is really only for people who are thinking of going into comp bio and maybe not catered as much toward others who might be interested in the major but want a different career path unless they want to take comp bio as an elective without all of the coding concepts. It would also maybe be cool to have a way for comp bio majors to do research in comp bio labs and get credit for it to go towards the comp bio degree.

• N/A

• Actual application of the concepts we learn

• I think more application of actual computing in the major would be a good start as the CS classes feel like they want us to be data scientists and not computational biologists. Machine learning should be part of the program, and so should physics, and something even more advanced like cell biology. I think the degree requirements could be tougher and should be tougher.

• Nothing

• To have more resources to seek for students to prepare their careers

• The introduction class for coding is “Introduction to python”. Somehow the intermediate class turns to JAVA. Why not set the primary class just aiming at JAVA since all the high level courses of coding are based on JAVA?

• The real life experience.

• I think understanding that this program is always going to need to be changed in some form every year since the field is constantly growing and new techniques and algorithms are being created that makes others no longer the industry standard

• Allow more opportunities for research, internships, and careers. There are little to no tables for comp bio at the career/internship fairs.

• Research opportunities for undergraduate computational biology students. More python classes because the java classes we have to take aren’t career–relevant. Also we only have 2–3 actual computational biology classes.

• Because this varies for majors and non–majors, I would emphasize which skills would be particularly useful for bio people and comp people, and comp bio people. This was already touched upon at the beginning of the semester, but I think this could be further developed a bit more.

• Providing everything computation al bio entails, specifying what it is/makes it different from bioinformatics or systemic bio. Also career opportunities and applications

• I am not a comp bio major, but this class made me consider it so I feel like it prepared me well.

• Incorporating more math courses could be helpful to the undergraduate major.

• More comp bio courses and don’t have them be only in one semester or alternate each year (I understand the major is small and new but still)

• I am not a computational biology major

• Make BIOSC 1542 and 1544 available both semesters or both in the same year. Add electives that incorporate computational aspects to biology more.

• Since the biology is easier to learn later on, I think the emphasis should be more on coding when it comes to the curriculum. More guidance towards internships and research opportunities always helps. I also think that the computational biology class definitely should be more marketed towards majors, rather than just an elective. A good foundation with coding and algorithms is super important.

What additional resources or support would enhance your learning experience if you wanted to pursue computational biology as a career?

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• I’m not sure, I think that the courses do a good job of introducing the field.
• Having a textbook, or being able to have access to to the main course concepts in a physical and centralized form would be helpful. However, I recognize this is a relatively new field and those might not be available.
• I would like to see more career, research, and internship opportunities.
• There are so many topics in the field and they all require really high–level knowledge to understand, and you tried your best to simplify things but at times I still found myself kind of lost around many of these topics and/or only having an extremely surface–level understanding of it, especially due to lack of resources online besides scientific papers which can be hard to understand. So I think your “omics breadcrumbs” website is a great idea and I would have loved to see all of the topics in it.
• More research opportunities provided through the school.
• For this major in particular, I think both research and bioinformatic software (Biosc and Cs 1640) should be necessary for students, I think both are rather necessary if we are to really pursue a career in this field. I think if both courses were required, albeit being a harder major, it would prepare students for what comes after. Machine Learning in this context also applies, if there is an in depth ML course about how it is being applied in C–Bio careers.
• no comment
• More of a focus on programming because the biology half is focused on more.
• Enough research opportunities and industrial connections.
• More python and coding classes tailored to computational biology majors.
• More connections and career guidance.
• N/A
• connections to research, internships, and coding based computational biology classes, more opportunities to apply computational biology concepts
• Study and practice material outside of class would’ve helped
• Perhaps having a professional internship system, somewhat similar to the engineering schools coop program.
• I think if there was more Python and more openness from research faculty it would make it easier. I think that, even if it was as simple as research faculty going to a class and giving a talk about what they do for 5 minutes, it would make the major feel more accessible. The lack of Python, especially as it was cut from the base Computational Biology course, makes it harder for a student not in research already to understand the expectations, and they can’t realistically get that knowledge until late sophomore year at the earliest.
• Maybe more information about what it means to join industry, what requirements you need, and general career paths.
• Some kind of event for computational biology majors to make more of a sense of community, and just more resources being put out overall.
• More research internship opportunities etc.
• CAREER RESOURCES!!!!!!!!!!!! Literally the very first time ever that anyone had ever mentioned anything related to computational biology and its careers was your class and the very first lecture. Talking to advisors is literally useless because it feels like they don’t actually know anything. They are just like listening to me and nodding their head….. like give me somethingggg. I think that more opportunities to take Python programming–based classes would be really, really great as well. I think that is something I am really missing, and as someone that didn’t come to college with a programming background, I feel that it is something I am pretty insecure about in this field.
• Career guidance and easy opportunities to do research with faculty at Pitt.
• Specific advisors that have greater connections to comp sci in addition to biology; more resources available for career opportunities.
• Internship help would be nice. I have applied to so many internships, but have been widely unsuccessful.
• .
• A club or a organization that meets weekly and teaches coding related to the field of computational biology
• There should be catered counselors or people with experience in what computational biology can be as a career. As a student it is hard to understand what I plan to do in the future especially because of the limited resources, but I find biology and computer science as fascinating subjects and want to use them both in my career.
• At least through the Department of Biological Sciences, I think it is kind of hard to lump in comp bio with the other majors in that department. Although the biological sciences advisors are wonderful people, I don’t think they are very knowledgeable when it comes to such a niche career. It would be nice to have advisors who have backgrounds in comp bio to help guide students through the major. I know some of the other departments in Dietrich do have some of their professors be students’ advisors, so I think that could be a possible suggestion.
• N/A
• NA
• None
• More practice questions or more exercises in class
• no
• More in class time learning how to use resources like PyMol
• More networking opportunities to find jobs in the field that aren’t just for research.
• Research, Grad school information and preparation, Shadowing, information on possible careers in both academia and industry.
• I really liked the introduction to Kaggle, as this was helpful for someone who has no prior python experience.
• info events
• Encouraging students, especially biology students, to take this class earlier in their career may spark interest in pursuing a comp bio career.
• It would be helpful if there were more information promoting the major itself because I had not known about it until a couple months into my freshman year, hearing about it from a source outside Pitt.
• more courses
• I am not a computational biology major
• Teaching me how to actually run the programs we learned about in Python and not just web–based applications.
• Help building industry connections, as in fairs for computational biology or bioinformatics or something close to that. I also wish there were more clubs or organizations that were geared towards computational biology majors who are interested in PhDs and Master’s, not just pre–meds.

Based on your experience in this course and understanding that I am applying for a teaching faculty position in computational biology, please provide feedback about my effectiveness as an instructor and my potential contribution to the department’s computational biology teaching mission. Your feedback will be considered as part of my application evaluation.

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• Alex provides detailed but not convoluted explanations of topics that may be difficult or confusing. Lecture material is presented in a way that is easy to understand and to refer to since there is not a lot of outside, readily available information about some topics. He has demonstrated a comprehensive understanding of the field as a whole and has constantly updated us with recent findings and publications, which is essential due to the rapidly evolving nature of computational biology. He can answer questions effectively and provide career advice to anyone who may ask.

• Good lecturer and provides lots of resources but could slow down lectures and simplify them a bit more because it was harder to grasp some concepts. providing lecture slides before class so people know what to expect would be good.

• As an instructor I felt one of the biggest strengths you had was keeping the content engaging. Some of the concepts covered with pretty advanced and difficult, however, you kept lectures enjoyable which helped me stay engaged when I would usually zone out. Outside of the classroom you work with the computational health science club, and while the club is still new I feel like you are helping guide it towards something bigger that will help all computational biology students.

• The content taught is good and relevant for a proper introduction to the field. However, sometimes, it is difficult to follow the content that you’re teaching in lecture at such a fast pace, or sometimes its disorganized, which I understand since its your second time teaching the class. Once the class becomes more structured and developed it should be fine.

• I think Alex did a good job of explaining computational biology concepts in a way that was easy to understand in lecture.

• I hope you get this position!!! I think you’re a great lecturer that can contribute a lot. I really like your “omics breadcrumbs” website and think that it’s a great idea. However, I think sometimes your expectations of us can be a bit high, and there’s very few resources for this class, so I do find myself struggling (especially on the final project).

• Alex is a good teacher and seems to be really passionate about the computational biology field and teaching others about it.

• I think Dr. M is a great professor. He provides many opportunities for students to seek help if necessary, and show off their understanding to him if not. I found him to be a rather approachable person, and he also makes sure to provide the most optimal answers. He is also very passionate about what he teaches, and that makes it a lot easier to follow the class.

• Dr. Maldonado is a fair, smart, and overall amazing professor. He is one of the most knowledgable teachers I have ever had and inspired me and will definetiley inspire those to come in future classes to want to explore the field of computational biology.

• I thought you taught very well and explained complicated concepts in a way that makes sense.

• Prof is knowledgeable enough as an intro CompBio teacher. He’ve tried his best to introduce the full spectrum of CompBio. The only thing I want to sugget a change is the richness of content (which I think is a bit too much for me as a sophomore).

• You explain and are very knowledgeable about the concepts you teach. In addition your work in the field provides good insight into real applications of learned concepts.

• You are a very effective instructor and would excel if given the chance to add more to the computational biology curriculum in other classes.

• Alex is approachable outside the class, willing to help every student in the class. In terms of teaching an lecture, I think it would be better if he can explain things slowly and more clear. Exams are okay but the multiple choices are hard to read and too tricky.

• First and most importantly, this course is open–source and accessible to anybody on the web. It is refreshing to see that for the first time, especially for a course that teaches the fundamentals of drug design, a common good for humanity.

  Speaking further to Dr. M’s integrity, he spends an incredible amount of effort on every little aspect of the course, going every extra mile there is to cater to the smoothest possible student experience. I have genuinely never seen anybody work so tirelessly on a project. It is built from the ground up in a medium independent from canvas, which, needless to say, works much better. I’ve even told him that he’s clearly going above and beyond what’s required, and in response, he proposed a plan to restructure the entire curriculum, integrating Python lessons into every lecture—a change I fully support and believe will make the experience even better.

  But that is not to say Dr. M is unreceptive to feedback. In fact, he is the only professor to my knowledge who asks for direct feedback on lectures. He recognizes that growth doesn’t come from getting everything right the first time, but from continuously refining and improving.

  In lecture, we did not learn any false conceptual frameworks. Instead, we were made to understand how complex things actually work, just presented in a clear, digestible way. This method, in my opinion, is far more effective than the traditional approach of learning things in overly complicated (and often flawed) ways, only to have to unlearn and relearn them later.

  Needless to say, there were no problems with office hours or emailing for help, which I certainly needed much of. At the risk of sounding arrogant, this has been the only course that has challenged me academically. With just one semester left until graduation, this is my lowest–performing course, but that doesn’t mean I didn’t learn a tremendous amount or thoroughly enjoy it. Quite the opposite—I’m grateful for the experience, and I highly recommend the course to anyone who wants to learn how bioinformatics and drug design really works.

• I think I did learn a good amount in this class (despite me having a difficult time grasping most of the concepts), and I appreciate your consideration for other students, making adjustments to class structure or the way that some of the information is presented in the slides. The use of a class website was very helpful in keeping the information organized. I think it would be beneficial to have the lecture slides looked over in more detail and prepared and posted earlier, and provide more practice for the exams and how to approach problems.

• Your class expectations were very clear and unit organization was effective. Your use of visual elements aided in understanding and your talking was clear and well paced. It was clear you knew the information well, were confident in your knowledge, and could answer questions with an in–depth response. The notes left on homework assignments were useful in improving for future assignments. I feel that you could improve upon your planning as some slides contained errors that you realized during class.

• Good at lectures, really prepared for every lecture and managed to make very content heavy lectures fun, kind of a hard grader in assignments but exams were very fair. I think you should provide more study material and practice material, it was really challanging to study for your class outside of lecture.

• Excellent instructor, extremely knowledgeable and approachable. Really goes out of his way to promote student interest in the computational biology major, and encourages student success.

• I think that it was obvious you cared, and that the effort put into the class definitely had a positive effect. I feel much more confident about my interest in the subject now, and I think that this class was an overwhelmingly positive experience for me. You seemed prepared for lectures, and down–to–earth and approachable. While some of the material was harder to understand, I think the way you presented it made it easier to pick up.

• I thought that the teaching style was mostly pretty good, though often the amount of content felt overwhelming (though I generally got it in the end, studying on my own ). I also found student hours to be incredibly helpful, as getting a second, different and slower explanation of certain concepts was incredibly helpful.

• I think that you were a very good instructor and put visible effort into helping us understand the content. I think there were some points at which you assumed people had a lot of understanding of topics that were pretty confusing. Also, some of the homework questions wanted depth in the answers that was not gone over in class, and it was hard to find information on the internet. Overall though, I think you were a good professor and have a lot of potential to improve even more considering you are fairly new and the computational biology major is also new.

• First off, thank you Professor Maldonado for your instruction this semester. I think your teaching was good I liked the idea of top hat questions through the lecture, I liked your analogies a lot most of them were very good. I think the switch you did by the end making the assignments have a word limit and the criteria being a little more clear was good but maybe do that from the beginning.

• I think 100% as someone that actually has a background in computational biology, you are an addition that we absolutely need in the computational biology department. It feels like there is such a low level of knowledge of computational biology within the bio department, and you are the only person that has actually given us guidance relevant for computational biology majors. I think that you are really doing your best to teach us a lot, and I think that I really learned a lot in this course. You exposed us to a lot of important relevant concepts, and compared to what I heard it was before, you did a lottttt. You address a lot of things that no other course had really taught before and I think you were a really great resource to us and preparing us for success. Like I havent never used anything I have learned in organic chemistry in what I am doing right now, but I KEEP applying topics I have learned in this course to what I am doing everyday in research.

• You’re content delivery was great You interact well with the students. However, I feel like towards the end, the content delivery rate was increased and I started struggling to understand what was being taught.

• Very understanding professor in situations that were outside of my control; engaging and funny in class; willing to adapt the class to the student’s opinions and in their best interest; very knowledgable about the field. I really appreciated the career advice that he gave throughout the semester. It is very helpful to get that information from someone who understands both the industry and academic worlds of comp bio. Overall really great professor. I wish I could take more classes with him!

• I think that you would be a great fit and you are giving students an insight and understanding into the computational biology world. There are some things that could be changed about how the course is structured and taught, as I previously mentioned, however.

• I think your slides were very engaging and understandable. You taught pretty well, and was always open to answering any questions. I do think you went slower in some parts that you could have gone faster, and faster in some parts where I think it would have been better if you went more in–depth. Overall, I thought that some of your best teachings were in the exam review lectures before each exam. I really felt that youn explained stuff really well during those times.

• .

• As a comp bio major student, from my perspective Alex done an amazing job as an instructor. He has opened doors for aspiring computational biologists. He introduces fundamental concepts and equips us for future courses like simulation and modeling. His clear and effective introduction to the major equips us with resources to enhance our self–preparation for future careers.

• I believe that there should be a better understanding of the students in this class and how to cater the best way to teach and convey the concepts of computational biology. With the pace and content of this class, it was very hard to grasp what was happening especially with only foundational knowledge in biology and chemistry. With the no python requirement, it felt like there was heavy reliance on the concepts that require so much more knowledge than just foundational science.

• I believe that Dr. Maldonado is extremely passionate about the material he is teaching, and it translates to how he teaches the course. It is really nice to also learn from someone who has a lot of knowledge in comp bio and does research in this field. Dr. Maldonado was very accessible, and his office hours were great for better understanding concepts. The material is hard as I expected it to be, but I did walk out of this class with a lot of new knowledge about comp bio as a field as well as career.

• N/A

• Alex is an amazing professor. He makes sure you understand the concepts by simplifying them and building off of that knowledge.

• It was obvious that our professor is extremely competent through his lectures and explanations. There was never a question he couldn’t answer, and he always had recommendations for your success if you asked. He’s an extremely ideal professor who accommodates everyone (Programming+)

• None

• I think that your effectiveness as an instructor is good. I liked how the structural biology section was structured and I liked the content we learned. The teaching style was good one imporvement is that the rubric of how homework assignments should be done to be more explicit and more detailed.

• Professor is a nice person and is kindly available to students.

• I would say it was decent. It is clear that you have a lot of experience, I just wish you slowed it down so people with not that experience could follow.

• I think how the topics were explained allowed me, who only took CS0011, to gain a much deeper knowledge of some of the tools I’ve used in the past. Though I did feel like a bunch of these more algorithm–based concepts went over my head I felt like I could go and ask a question and receive a very insightful comment and gain an understanding.

• I feel as if the professor was not able to convey the material properly. It was hard to understand lectures, and the slides were of no help. There was little to no supplemental material to turn to.

• Professor had deep understanding of the course material. Lectures were decent, a bit heavy. Assignments were relevant but harshly graded considering the length restrictions and limited resources. The exams were ok, but the wording for the questions and all the multiple choice questions was unnecessarily complex and confusing, so it was difficult to tell if your answer was correct even if you knew the course material. Also didn’t give clear example of format for open–ended responses (had multiple different formats in the slides), then penalized when it was formated one way that was in the slides vs. another way that he didn’t specify was required. The project is very good and useful application that I am enjoying so far. I also liked the python classes at the end of the semester.

• I think Dr. Maldonado was a really excellent instructor. The content was delivered clearly, and made accessible in multiple formats immediately after lecture. The homework and exams were directly related to the content presented, and he always made room and time for questions. Additionally, he was always available in person and online outside of class and was extremely apporachable. In an academic environment at this level, it is refreshing to have an instructor who does not look down at you, but rather wants to build up his students to prepare them for post–graduation. Dr. Maldonado is additionally very knowledgable about the work and research opportunities within the greater Pittsburgh area. He has made this educational experience very enriching and supportive. After this class, I feel very prepared for the next steps in my research career, and have gained interest in computational biology as a potential career path.

• effective overall beneficial office hours slides were always posted and homework was manageable

• Alex is truly the best teacher I have ever had at Pitt. He is so easily accessible for office hours, over email, and after class for general questions. He is also energetic and very approachable which makes his class that much more enjoyable. With this being said though, I never felt like I could skip his class because the material was easy, but I never minded attending class because it didn’t feel like a chore.

• I believe Dr. Maldonando did a good job at explaining difficult topics in simpler terms. Since this is an introductory course and actual computational biology is incredibly complex, it is vital for the professor of this class to be able to look at, to interpret, and to explain this content to less knowledgable people, which was done well in this course.

• you teach well and make things clear just go over your slides in advance

• I believe Alex really cares about his students. His teaching can be rocky at some points but it is clear it is from lack of experience and he works hard to learn. He accepts feedback from students and clearly wants everyone to understand the material and succeed.

• This class was genuinely so boring. I fell asleep almost every lecture I can’t lie, I had to chew gum to stay awake. Dr. Maldonado would get himself on tangents frequently, and I felt like he talked down to us instead of trying to talk to us as an educator. He had this vibe about him that came off as “I know everything about computational biology and therefore none of you know anything, and I am always right”… when he is not a computational biologist by trade. It was very condescending, and the way he spoke to us did not make me want to engage with course material. Additionally, he would gloss over some topics, and then would ask us questions about them on exams. It did not feel fair, especially when some of the nitty–gritty details he would test us on were not in his lecture slides. Also, he speaks very fast, and I often had a hard time taking down notes as he was lecturing without falling behind.

• The professor is very flexible and accommodating with students. He answers every question with thorough explanations if you ask him during lecture or office hours, giving examples and explaining things on the board too. He is also very approachable which makes it easier to ask questions. I think he did struggle sometimes covering large amounts of content during lecture, but he genuinely wants students to succeed and just needs more experience.

What aspects of the computational biology major have been most challenging, and how could they be improved?

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• I think the beginning of the course had some challenging material, but I think focusing on the conseptual parts was good.
• the actual coding that we will be doing would be good to know and practice
• I felt like some of the science concepts were a little challenging. I had a rougher time in Biology 2, so I probably would have benefited by waiting till I had taken some more biology classes like genetics before taking this class. Possibly suggesting a higher level science class be taken before this class might have been helpful, but not everyone would really benefit from that.
• I feel like a lack technical skills and hope the more technical and practical skills an be taught early on rather than later in the undergraduate years.
• The field is just so broad and so deep at the same time, with so many different topics that all require high–level knowledge to understand. Also, doing the practical applications is pretty challenging and high level as well. I’m not sure how this can be improved aside from more specialized courses and providing more resources (please!!). At times I find myself both clueless and helpless when a question or topic isn’t something we directly covered in class because I struggle to find information about it online aside from a few papers that only complicate it more and there’s no resources provided for us in this course aside from the slides (which can often be vague and/or not cover the question), and it can be very frustrating.
• The computer science courses are sometimes pretty difficult, maybe only required some basic level courses would be easier.
• I found exams to be rather heavy in content; there are too many topics and this makes studying for them rather hard. I would recommend increasing the number of midterms, and perhaps having 50min lecs instead of 75 min ones. A recitation section which is strictly for preparing for midterms/finals would also be nice, opposed to a recitation that is for the project.
• I think all of the first unit, but thats because I didn’t think this was going to be a full on computational biology course. It was and I was wrong. This class felt like it taught me the mojority of what I needed to succeed in this field and i was not prepared at the beginning. I feel like others definetely felt the same thing so clarifying that at the beginning would be very helpful, and not to scare students away, just to prepare them that every lecture needs to have full concentration.
• I think it goes too in depth with certain topics without having actual practice with tools/applications to help with understanding
• It takes time to dive deeper into concepts by ourselves. I would like some more guidance on self–taught progress.
• I think the coding parts. I also struggle with application of material I learned.
• Personally, it is the coding part. Since the job industry require us to do more python an r, we should have focus on that instead of bunch of java stuffs.
• N/A
• Understanding the concepts of computational biology. I am really not sure but I think if i took more classes as a prerequisite to taking this course I would understand it better; a lot of the algorithms and math–based concepts were confusing to me. Maybe if the course required some coding I would understand it more.
• Understanding how to use and read the current databases needed to do most situations and construct models. Spending some extra time teaching about the use of these resources could improve this.
• Bioinformatics, probably including coding could have helped
• Many of the co–reqs for the major, in particular the chemistry/biology co–reqs, are heavily geared towards the MCAT and are brutal! Some of the CS co–requirements are tediously dry. Having additional major specific courses would be a welcome respite for comp bio major students.
• It feels like the people in charge of the program don’t know what they actually want the program to be. As I’ve mentioned before in this survey, the lack of department support for increasing programming inclusion makes it feel almost like the department wants us to fail. Also, some of the required courses are important, but from how those instructors speak, it’s obvious that they never think about this program or any similar ones (I think clearly of how in one of my courses, which had a large pre–med section, my instructor had us memorize something solely (in her own words) because it would also be on the MCAT. I am not planning on taking the MCAT.) I feel like because the program is so small, it’s not well–known, and it feels like the people controlling it don’t want it to be well–known or advertised. I only found out about the major because a friend of mine is also majoring in Computational Biology.
• I cant think of anything specifically difficult, besides hard classes which is to be expected.
• I think the most challenging part is making the major feel more cohesive because the coding classes are a lot of Java, and it seems like computational biology classes are going to use a lot of Python. Additionally, the pre–requisites for this class were basic, but I felt like some of the topics dealt with a few things going on in classes I’m taking right now, like Organic Chemistry.
• The exams are very challenging to me at least the multiple choice answers some of them will be obviously wrong but sometimes 2 answers will be almost impossible to discern that is my opinion however and maybe due to not preparing enough however I believe I prepared enough and knew the answer generally but sometimes not to the level that the question required.
• Taking courses that are actually relevant to this major. I personally think the entire major needs to be relooked at and revamped so we are actually learning more relevant concepts.
• Simulations. Not sure because this is my first Comp Bio focused aspect.
• Finding outside of classwork extracurriculars like internships.
• .
• I think the mathematical parts are challenging, I can’t understand the equations introduced with knowledge in cal 1. I feel like the department need to recognize the importance of mathematic to this major and includes more mathematics courses related to this major.
• Almost everything. Teaching needs to be at a manageable pace.
• It is definitely a lot to cover all of the science core courses, CS core course, and computational biology core courses. I have found having to do science and CS classes has been rather difficult in the same semester, but you can’t really put either of them off because to do the computational biology major, it is very helpful to have some classes in science or coding under your belt already. Pretty much all of the classes are important, so I’m not exactly sure how they can be spread out to make the class load a little bit lighter.
• N/A
• Certain concepts were challenging, but having the lecture slides beforehand would help me better understand and learn what we do in class
• As of right now, a lack of practical application until taking a second course in CB could be something that’s improved upon. I also don’t know if this course was more challenging because the semester was technically accelerated.
• None
• The genomics part it could be improved with more detailed explanations
• I think is coding. It is better to set up coding class especially for ComBio students.
• The lack of experience for real world
• I don’t know since I’m not a comp bio major
• Combining the comp and the bio. Could be improved by offering classes that combined the two.
• limited resources
• In my opinion, the matrices and the computational techniques we learned for sequence storing were challenging. I think they could be made more accessible by extending the time we took to learn them, and perhaps work through more in class examples.
• the implementation of coding and physics into all the different models and simulations
• The most challenging part of this class has been the applied project aspect, but like I said earlier, Alex is very accessible and will help you as needed.
• The toughest portion of the major has been balancing a combination of natural science and computer science in my coursework, but it is possible with just a little extra effort.
• more practical stuff and practice
• I am not a computational biology major
• The fact that I only take four classes that actually center around CS + Bio together, and otherwise it’s a CS minor + a Bio minor + supplemental math and chemistry… I worry I am not qualified to actually pursue this as a career.
• This is more personal, but having to take organic chemistry and computational biology in the same semester has been extremely stressful and challenging. The coursework is definitely challenging when there is a need to take natural science and more coding related courses. I have heard that organic chemistry and chemistry in general is really not used that much in the field of computational biology. I think that like how engineering majors have a separate chemistry course designed for them, as well as different tracks depending on whether or not they want to do something related to chemistry, it would help if there were chemistry/organic chemistry courses designed for CompBio majors that are more suited to their careers and not just “weed–out” courses to challenge or test them. Something that is like computational chemistry would be a lot more engaging and I would feel motivated to work for this, since I know I will be using this in the future.

What are your career goals after graduation?

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• Research in pharmaceutical sciences
• Medicine.
• grad school + job
• After graduation I either want to attend graduate school to study genetic counseling or become a software developer.
• I’m hoping to purse an MD only or MD PhD in some area relating to computational biology for the PhD portion.
• Grad school
• I am a computational biology major and I was originally thinking of heading into the computational biology field, but now I realized that I would rather not do anything biology–related if I can manage it, and that I would also only like to achieve a bachelor’s, if possible (so no Masters/PhD program unless I am out of options), though I will stick to this major still. (This is not your fault/the fault of this class, just a changing of my personal goals)
• I want to attend dental school
• Masters, PhD if possible, then I am escaping to industry (I wish to buy a house before I am 30).
• I don’t really know. I plan on getting my masters but in what I am not sure yet. I switched my major from comp bio to marketing but I loved this course and want to do something like it in the future so I think I’m going to get an internship, graduate, then keep working until I decide what i want to master. Currently definetley something science related. Medical or pharma sales is my ideal job right now however, if I can I would also love to be a computational biologist.
• A programming job, hopefully with medical applications such as protein analysis or genetic sequencing.
• Master Degree
• I am on the pre–med track and want to continue with that
• PhD in computational biology or AI in medicine.
• Dentistry
• I am really not sure about whether or not I want to go to grad school––I would like to get a tech related job. If I do end up doing grad school, I would want to work in the biotech industry.
• research
• I would like to pursue graduate school.
• I am currently planning on entering academia, with an end–goal of teaching at the university level.
• Graduate school, and go into some kind of research either academic or in industry.
• PhD in biochemistry, then industry/academia
• I want to get a Master’s degree or PhD.
• We’ll see I am currently comp bio major pre med one of those will be my career in my opinion but I’d like both skills so that I may choose at a later date
• INDUSTRY!
• Become a research PhD focusing on Bioinformatics
• Most likely to go for med school and possibly be a physician.
• Going into the pharmaceutical/biotech industry.
• .
• Pursue a master’s degree in computer biology, possibly even a Ph.D.
• Masters in computational biology or data science
• I would like to go to physician assistant school after graduation.
• N/A
• Bioinformatics, SWE, grad school, etc
• Grad school
• To get into medschool and become a doctor.
• Applying for master or PHD degree.
• Med school
• To work in industry before going to med school
• I would like to get a job in the industry or go into graduate school.
• grad school, probably in bioinformatics
• I am pursuing my PhD after undergrad.
• unknown
• Apply for jobs/enter the work force.
• My main career goal is to attend medical school, but I do find computational biology very interesting and wish to learn more about it.
• PhD or MD
• Working in a biology lab
• PhD
• PhD and then work in either industry or research

What are the essential qualities of a successful instructor for computational biology courses?

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• Someone who has a deep understanding of the material as well as the field and how is is changing.
• A successful instructor for computational biology needs to be knowledgable and be able to effectively communicate. This class is not one where a instructor can just read of the slides verbatim and expect the students to understand everything when exam time comes, the instructor has to understand the content so that they can convey that information in an effective manner.
• Explaining things in a way that the concept is easy to understand without too much fluff/complexity that isn’t needed to explain the topic at hand well.
• I think that they should be able to simplify high–level topics concisely and also be sympathetic to the fact that many undergraduates may not fully understand many of these ideas or these programs.
• Respect, understanding, empathy, kindness.
• Being passionate and knowledgeable about what they teach, being approachable, I think they should also be human (optional), someone who does their best to understand their students and succeeds on education them should be a qualified instructor for these courses.
• someone who is very knowledgable
• I think balancing the computational and biological aspects of the major
• Explain concepts concretely and set appropriate richness of content.
• I think they need to know very integrating knowledge about the content, have in–field experience, and be able to simplify the concepts to people who have never been introduced to them before.
• Willing to help students without any background of cs or bio so they can feel comfortable in learning.
• Besides experience in computation biology itself, I think its the same as for any other course:, clearness in expectations, fairness, availability for help outside of class, flexibility / receptiveness to feedback.
• considers student opinions, a good amount of availability, able to simplify complex topics
• The ability to answer questions about fieldwork and the use of class material in a realistic context.
• Enthusiasm, knowledge, promotes problem solving ,respectful attitude towards students.
• Approachability, knowledge and the ability to share it well, motivation, and a compassionate attitude.
• Someone with a strong understanding of general computational biology ideas (modeling, and genomics), and a strong ability to explain everything assuming that students have little to no background in subjects other then basic bio.
• Being able to connect with students, having the ability to explain complicated topics at various levels, deep knowledge of computational biology
• Knowledge of course, ability to speak, these are more general however for instructors of anything. I would say a genuine enthusiasm for the subject which Professor Maldonado has as he would frequently review things himself and research throughout the semester.
• The ability to explain difficult concepts in a digestible way. Experience wihtin the computational biology field i think is a MUCH – that is how we can really benefit in terms of career and academic path insights.
• An interactive/not–boring delivery of the content. Otherwise people will struggle to understand what was being taught, and since there are no textbooks, they flat out what understand the topics.
• The ability to break down complex topics so anyone can understand them. Also the ability to connect different topics to each and why we are learning something and how it relates to the previous topic. The reason is due to the sheer amount of complex topics required for a one–semester course.
• Focus on getting you the knowledge needed to actually apply your education and get an actual job.
• .
• To simplify the concept and make it engaging, while simultaneously imparting programming skills, Alex has excelled in all these criteria.
• Knowing what students have learned and how to go further to teach more but at a manageable pace
• Someone who is very accessible, is knowledgeable about the content and has a background in comp bio, and someone who is able to reduce more complicated topics into something undergrads with less background could understand.
• N/A
• I think someone who is currently active in the field and still learning and up to date about the field is necessary
• Nice person
• Good explainier, good coder, expert in the field.
• Have strong biology and coding ability
• Helpful, ability to reach out with him, knowledgeable
• I think someone willing to put in the work and make a big effort for their student’s success.
• Wanting to help their students get better
• Essential qualities include patience, and ability to explain complex concepts in digestible words.
• understanding of content as well as what students can and cannot understand right away
• Knowledgable, accessible, approachable, confident
• The instructor must be well–versed in the topic but also be able to effectively communicate what they know to beginners.
• Can teach well and adjusts to the students needs
• Being able to explain concepts to students of all different background – both computer science and biology
• Someone who is engaging, willing to push students, and has ample practice for real–world applications of their course material.
• Approachable, engaging, flexible, makes the class more conceptual and problem–solving based rather than heavy memorization.