Computational Biology Seminar (Fall 2023)

Semester: Fall 2024
Website: pitt-biosc1630-2024f.oasci.org
Meeting time: Wednesdays 1:00 PM - 3:30 PM
Location: 302 Cathedral of Learning

Grade distribution

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Below is the final grade distribution of the 21 students in the class.

A+ (42.9%)

A (33.3%)

A- (0.0%)

B+ (0.0%)

B (9.5%)

B- (0.0%)

C+ (0.0%)

C (4.8%)

C- (0.0%)

D+ (0.0%)

D (0.0%)

D- (0.0%)

F (0.0%)

S (9.5%)

NC (0%)

Teaching evaluations

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The following passages are unmodified student responses (19 out of 21) to a Course Survey administered by OMET.

The standards the instructor set for me were

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Too low: 0

Appropriate: 16

Too high: 3

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

#

Less than one hour: 0

One to three hours: 4

Four to six hours: 12

Seven to nine hours: 2

Ten or more hours: 1

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

#

Strongly disagree: 0

Disagree: 2

Neutral: 2

Agree: 5

Strongly agree: 10

The instructor was prepared for class

#

Strongly disagree: 0

Disagree: 1

Neutral: 1

Agree: 6

Strongly agree: 11

The instructor treated students with respect

#

Strongly disagree: 0

Disagree: 1

Neutral: 0

Agree: 6

Strongly agree: 12

N/A: 0

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

#

Strongly disagree: 0

Disagree: 2

Neutral: 1

Agree: 5

Strongly agree: 10

N/A: 1

The instructor evaluated my work fairly

#

Strongly disagree: 0

Disagree: 1

Neutral: 2

Agree: 9

Strongly agree: 6

N/A: 1

The instructor provided feedback that was helpful to me

#

Strongly disagree: 0

Disagree: 0

Neutral: 2

Agree: 5

Strongly agree: 11

N/A: 1

I learned a lot from this course

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Strongly disagree: 0

Disagree: 0

Neutral: 2

Agree: 6

Strongly agree: 10

N/A: 0

The instructor creates an inclusive learning environment for all students

#

Strongly disagree: 0

Disagree: 1

Neutral: 0

Agree: 3

Strongly agree: 15

The course was intellectually challenging

#

Strongly disagree: 0

Disagree: 0

Neutral: 0

Agree: 10

Strongly agree: 9

The course stimulated my interest

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Strongly disagree: 0

Disagree: 2

Neutral: 1

Agree: 9

Strongly agree: 7

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

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Strongly disagree: 0

Disagree: 0

Neutral: 2

Agree: 5

Strongly agree: 12

I felt comfortable expressing my perspectives related to the class materials

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Strongly disagree: 0

Disagree: 0

Neutral: 4

Agree: 2

Strongly agree: 13

The instructor maintained an environment where students felt supported asking questions and seeking assistance

#

Strongly disagree: 0

Disagree: 0

Neutral: 4

Agree: 2

Strongly agree: 13

This course helped me learn to identify main points and central issues in this field

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Strongly disagree: 0

Disagree: 1

Neutral: 0

Agree: 6

Strongly agree: 12

This course enabled me to read research in this field with understanding

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Strongly disagree: 0

Disagree: 1

Neutral: 1

Agree: 7

Strongly agree: 10

This course helped me to improve my critical thinking skills

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Strongly disagree: 0

Disagree: 0

Neutral: 1

Agree: 10

Strongly agree: 8

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

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Strongly disagree: 3

Disagree: 3

Neutral: 4

Agree: 5

Strongly agree: 4

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

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Strongly disagree: 4

Disagree: 3

Neutral: 5

Agree: 6

Strongly agree: 1

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

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Strongly disagree: 5

Disagree: 3

Neutral: 6

Agree: 4

Strongly agree: 1

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

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Strongly disagree: 2

Disagree: 4

Neutral: 6

Agree: 6

Strongly agree: 1

Industry connections are readily available to computational biology students

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Strongly disagree: 5

Disagree: 6

Neutral: 6

Agree: 2

Strongly agree: 0

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

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• I like that the course centers around writing our own perspective paper, and the activities that revolve around reading and presenting the contents of published papers.
• I enjoyed the presentations, the fact that we were given adequate time to prepare, and the tips we were given afterwards on how to improve.
• Alex is one of the best professors I’ve had at Pitt. As a student, I felt that he truly wanted me to succeed and gain skills I could apply in my future, regardless of where my path takes me. I enjoy how the structure of the class encouraged collaboration and curiosity through the group presentations on Comp Bio papers, without placing emphasis on needing to know and understand everything. I never felt afraid to ask questions, and Alex would work with me until I felt I actually understood the concepts being discussed in the papers. Furthermore, he provided great resources and instructions for how we could structure our perspective papers, as well as detailed feedback on where we could improve for every individual part of the paper. The structure of the class ensured that we had ample time to put our papers together, and that we wouldn’t wait until last minute to try and write such a large piece. I’m not someone who usually has the time to revise my work because I wait till last minute to do it; by having deadlines throughout the semester, I was forced to prioritize my writing and then had time to fix it.
• I liked Alex’s flexibility and knowledge in many fields to help explore different papers and fields within comp bio.
• The course gave me a good understanding of the computational biology field as it currently stands, especially with focus on the subtopics I want to pursue. It helped me get better at reading scientific articles and improve my own scientific writing through the perspective paper assignment. Group work for paper presentations is well structured so that students have a good understanding of the paper despite them sometimes being very complex. Expectations for assignments are always very clear, and Alex has been willing to meet students where we are if there is a mismatch in what he expects and what we can deliver at the moment. Alex’s feedback is always very thoughtful and thorough, and he engages with students often to discuss what is/isn’t working about how he is teaching the class. He has been very flexible and has prioritized student feedback in order to meet both his teaching goals and provide what we are looking for from the class. Alex has cultivated a class environment which is comfortable and encourages discussion and collaboration. This allows students to freely express if we have concerns about any assignment or if we wish to take the class is a specific direction (for example, we are allowed to discuss deadlines and decide what kinds of papers we would like to learn more about). Alex has also made efforts to bridge the gap between the minimal coursework on computational biology methods most of us had prior to this course (earlier sections of 1540 did not prepare us well for the CADD topics we’ve been discussing in this course, and many of us have not yet taken our higher–level computational biology course). This has been largely by giving pre–lectures on a paper’s topic so that we have a foundational understanding before reading the article and encouraging pre–lecture assignments to skim the paper.
• He provided detailed and thoughtful feedback on assignments, which was very helpful. That said, the feedback was often given two days before or even after the next assignment’s deadline. It might be even more beneficial for students if feedback were provided about a week earlier, as this would allow ample time to thoughtfully reflect on the comments and make meaningful improvements to the next assignment.
• I like that our final paper was divided into multiple smaller assignments in order to encourage progress throughout the semester.
• I liked the regular feedback being given after each assignment. This helped me improve in each assignment.
• It taught me a lot of things that I thought were directly applicable to my continued education / career. I was never formally taught how to read academic papers or write them, and the skills I learned through Alex’s instruction has helped me tremendously outside of class in my own research experiences.
• I liked the level of input that students got to provide to class topics. For example, getting a say in topics we wanted to see in the papers we read, etc. I also liked the level of in–depth feedback we received on our writing assignments.
• I enjoyed the lectures, the presentations made me nervous.
• I liked that the writing assignments were distributed over the entire semester, and we received feedback. It made it less stressful to complete the the final draft submission.
• I throughly enjoy the setup of the course, with reading a different paper some weeks and presenting other weeks. I think it kept the course interesting and I also enjoyed all the open discussions we had.
• I liked that we worked on our perspective paper throughout the semester, so that we could work on parts of it before putting together the final submission. I also enjoyed working in small groups to understand comp bio literature. I think this was helpful to my understanding because it is always more demanding to try and find a way to explain something to others than to simply be tested on it. I feel like it also allowed for more collaboration and overall better retention. I also greatly appreciate Alex’s decision that if we are happy with our draft grade he will use it for our final. I think it makes a lot of sense.
• I liked that the course was set up with checkpoints during the entire semester for our perspective paper we needed completed by the end of the term. It allowed for ample feedback and guidance that was thorough and very helpful. More specifically, I have never written a scientific paper before. Additionally, I have read scientific journal articles on my own time, but have never had the opportunity to deeply read and understand these articles in other classes. Hence, having the checkpoint assignments for each part of our paper, as well as the professor’s thorough and clear feedback and guidance, greatly enriched my understanding and writing. Furthermore, having activities in class where we had to present and also read articles given to us that day in lecture was difficult, but is a necessary skill to learn. The way the course was taught gave me resources for the future that are so valuable.
• I really appreciated the way Dr. Maldonado would give us time to go through a research paper on our own, and then in groups focus on specific portions of it that we would present to the class. I felt that this was really helpful because it allowed us to individually dive deep on portions of the article, but still understand the whole thing since the presentations became very approachable and understandable since we had a very similar knowledge level of the content.
• Class time was structured fairly and well. I liked the topics taught a lot and found it extremely relevant to the field. This is the first time at pitt I felt like this was true for computational biology.
• The course structure was very good, I personally found a lot of value in how we were required to read, understand, and evaluate the strengths and weaknesses of papers during class. For me, this was very good practice in critically engaging with scientific literature, and I feel that my ability in this domain has greatly improved. The guidance given on searching for, engaging with, and presenting scientific literature was invaluable, and I feel that I am better prepared for my future career.

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

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• I would give some more time, maybe one or two extra weeks, to students to find the topic of their perspective paper, in the hopes of having each student narrow down to a specific perspective. I feel that once students have a thorough understanding of their specific theme and a logical flow of how to go about arguing this perspective, the writing portion will be much easier and less time will need to be given.
• I would say the time until we received grades was very frustrating. Although we had peer review feedback it just never compared to the feedback you gave us. I do appreciate that you would give us extra time when the feedback was late. I also didn’t understand the grading since sometimes you would grade some parts of my paper with no context from my previous parts. So then you would dock points at moments where you needed context from other parts of my paper.
• I think Alex was still finding his rhythm at the beginning of the semester and that lead to us not having enough time to really put in our best work for the first couple in class assignments. However, he was really understanding and receptive when we brought up that we didn’t have enough time, and was able to somewhat restructure the class to give us the time we needed. I think for future semesters, he could spend more time in the beginning of the semester teaching skill like how to give a presentation, create slides, and write a perspective paper (maybe have the class read a perspective on something related so they can understand the format).
• nothing!
• I would not make major changes to the way Alex has taught this class –– I have appreciated the changes he’s made and that he’s been very intentional with his decisions in teaching this course. Based on feedback this semester, I believe he will be able to design a better syllabus and schedule that meets students’ needs in the future.
• I would encourage students to explore a broad range of topics. While he did not explicitly prohibit selecting topics outside his specialty in molecular dynamics simulations and chemistry, he did not seem to actively support such exploration. While I respect his expertise in molecular simulations, I believe it is particularly important in an undergraduate seminar to foster an environment where students feel empowered to pursue diverse interests within computational biology.
• Depsite the fact that the smaller assignments helped encourage progress throughout the semester, it also led to me being significantly less knowledgable about the topic I was writing about for the earlier assignments as compared to those that came later. This meant I had to change the sources I found/used multiple times, as well as adjust my introduction, etc. It may help save students some time to try enforcing a stronger understanding of the paper’s topic at the beginning, rather than letting it continually grow while working on later assignments.
• I would explore more concepts in computational biology
• I thought Alex did a great job.
• I think I would be more consistent with assignments and grading. There were several pre–class assignments in the second half of the semester that were on the class website but never updated or addressed in class. Also, grades and feedback could sometimes take a long time to be returned, which is critical when sections of a paper that build on each other and are being graded rather harshly. Getting feedback from one section on Sunday at 2pm, when the next section is due midnight the same night was hectic and disorganized.
• I wish we could switch the groups around me, I sometimes felt left out.
• Since most of the students in this course did not get an adequate overview of comp bio from taking BIOSC 1540, I wish we had spent more time learning about different computational biology techniques, and then reading papers that showcased how these techniques are put into practice. I did not like how we split up into groups to present different portions of a paper because I didn’t understand the paper’s contents after the presentations.
• I would most likely have more lectures going through the methods described in the papers we read.
• I understand that this is difficult given the volume of students and fast pace of the semester, but I feel if we had started writing the paper sooner and gotten feedback on the individual portions we had written, it would not be as difficult to make all of those edits last–minute before the draft was due, meaning that more of us could have potentially submitted drafts that we felt addressed Alex’s concerns. I happened to have enough time that Sunday to address Alex’s analysis feedback that was published to me that day, so I did my best to address almost all of his comments, but I do know others in the class struggled with having little time to address the feedback. Alex did mitigate this by reopening the draft for more days, but I think some of the students that were stressed about not meeting the deadline may have been more relieved to know that information sooner.
• I would not change how the course was taught.
• I would just go over more perspective papers earlier in the semester.
• Focus more on how to write, this was my first real scientific writing course, and I already knew pretty well how to present slides and papers, but have never written a review before.

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

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• I think there should be concentrations for the major. Because I am pre–med I enjoyed this major because it gave me the flexibility to pursue something I was interested in while allowing me to take my prerequisite courses for med school. However, I do believe if someone wanted to go straight into the field, or even go to grad school some of the courses offered wouldn’t benefit that much. To excel in this career we should be required to take linear algebra, intro to machine learning, etc… In general more higher level CS classes that teach us python instead of java.

• I did not take Intro to Comp Bio with Alex and I don’t think I really understood what the field of Comp Bio is until taking this seminar. He did a great job introducing us to the major themes of Comp Bio by focusing on specific papers from the field. It’s somewhat unfortunate that this class is usually taken by seniors, because I feel like many students entering the Comp Bio major haven’t been exposed to what the field actually looks like and what they would be doing upon entering the field. I choose this major because I like coding and I’m interested in med school but wanted a backup path in case that doesn’t pan out. To me, Comp Bio seemed like it should provide some job security. However, I’m now unsure if I would actually enjoy doing the types of things that the Comp Bio field entails. It would have been nice to be given a better understanding of Comp Bio from Pitt before getting to my senior year; however, this could also be due to the Intro to Comp Bio class that I took with Brouwer, which had nothing to do with the actual field of Comp Bio.

  Also, I have no idea how the CS classes I’m taking actually relate to the major. They feel completely separated from what I’m learning through bio or comp bio classes and have no real practical applications for me. I’m taking BIOSCI 1544 next semester alongside BIOSCI 1640 so I’m hoping those classes will finally teach me something that I could use in the field, but once again I feel like this is too late in my academic career to be the first time I’m exposed to real life applications of Comp Bio.

• More focus on AI and data science, more classes with real–world projects and applications, more exploratory or helpful classes/teachers that cover different subjects and relate directly to computational bio. i.e. reading and understanding academic papers, and designing program

• I would recommend for the computational biology program to be further developed. The field is vast and the program is only growing, but there are currently few resources for students to gain a broad understanding of the the different subtopics. One suggestion is that it would be good for the 1540 curriculum to be more structured and better prepare students for these higher–level computational biology courses. The 1540 section I took had greater focus on data science and global human genomics, with almost nothing about CADD. As a result, I ended up learning most of the techniques used in this field through my research or in seminar. The program should either be refined to focus on a select few critical applications in computational biology or provide an overview of the various subtopics so students are aware of the different paths/what might be best for them. This way, computational biology students required to take this seminar can spend more time honing our scientific reading/writing skills and diving into more specific aspects of the field rather than having to spend time learning the basics.

• I deeply appreciate the Pitt Computational Biology program’s strong foundation in biological sciences and chemistry. To further strengthen the program and enhance its future potential, I believe incorporating greater emphasis on physical sciences, such as mathematics, physics, and machine learning, could be highly beneficial. For example, incorporating a dedicated machine learning course would better prepare students for careers in this rapidly evolving field. Additionally, adding courses in physics and mathematics, such as PHYS 0174, 0175, linear algebra and differential equations, as part of the curriculum would provide a more comprehensive foundation. Since these courses are currently offered only as electives and not mandatory, I believe that only individuals who are already actively pursuing related fields are likely to recognize the importance of these prerequisites. Making such courses a more integral part of the program would ensure that all students develop the necessary foundational knowledge to succeed in computational biology and related fields. Integrating these topics into the program would not only align with current industry demands but also position students to excel in computational biology careers.

• Providing more opportunities/examples of ways students can use their degree progress to get involved with research and other extracurriculars while still an undergraduate.

• There can be more curriculum relating to the industry and its applications.

• I wish we learned more about machine learning and computational tools implemented into biology. I felt like the computer science core and the biology core were very separate, and too few classes focused on their intersection. We had computational biology and computational genomics, but even the application in those courses could have been further explored. I think the cirriculum needs constantly revamped to prepare students to enter such a dynamic field

• I think most of the program needs to be workshopped for computational biology. Upper level courses in Java are largely unhelpful in the field. Not many courses focus on R or Python, which are necessary. Many programs require courses like linear algebra and machine learning, which are not required currently.

• Help them get more experiences, more hands–on learning

• The whole major feels like it’s an afterthought, there aren’t consistent professors teaching the courses, and we do not go into depth for a lot of concepts. I feel like I have a general understanding of the field, but no practical experience.

• I think extra elective classes need to be added to the curriculum that are highly recommended such as machine learning and linear algebra. There also needs to be less cs courses and more actual computational biology courses since the cs courses such as taking two semesters of data structures seems unnecessary. Discrete structures also seems like a highly unnecessary course since I have not used the material anywhere else.

• The only classes I have learned computational biology from at Pitt have been BIOSC 1540 and BIOSC 1630, both taught by Dr. Alex Maldonado. Other than that, none of my computer science classes integrate any sort of data analysis or biological applications, and the kind of coding we do is very different from what Alex has told us computational biologists do. As such, we are not prepared to enter the computational biology workforce.

• We are required to take core biology classes and core computer science courses, however there are very few courses, like this seminar, that are able to tie together both fields. More specifically, more machine learning based courses and less java focused and more python–based courses would be much more useful for our future careers. I think more computational biology specific courses where we can apply our understandings from other courses, would be very beneficial. Additionally, some of the courses feel like they do not flow as well together. For instance, the first computer science course I was required to take was Intro to Computing for Scientists. This was a python based course, which gave me the foundations I needed in python since I had never taken a CS course before. The next course after this was Intermediate Programming, which was entirely java–based and we were given no foundations in java, which made the course and transition to java much more difficult. Overall, I think more computational biology specific course would be beneficial.

• I think there are several improvements that could help. To start, I think the major progression sets you up to have either a really strong biology background or a strong computational background, but doesn’t effectively integrate the two until much later in the major. Also, there is only one upper level class that is required to be taken, which further makes it feel somewhat like a dual degree between biology and computer science. Also, the introductory course not having a coding prerequisite hurts computational biology students, as it doesn’t teach you how to apply a lot of the fundamental concepts that we learn about.

• You seriously need to listen to people with experience like Dr. Maldonado. Especially since the school of medicine has such an amazing Comp Bio phd program. It is actually ridiculous how terrible the undergrad major is right now. I learned anything and everything practical from the school of medicine by doing research. Please stop screwing people who want to get into this field but do not know enough originally to know if the program is good. Listen to Dr. Maldonado. He is genuinely the only person/ class where I learned something useful. There needs to be major change here. Without my research opportunities in the school of medicine (which are few and far between in terms of opportunities, I got really lucky), I would have basically just been useless in the job market. Fix it please.

• The education in python programming feels very disjointed. The order of courses required for CompBio feels off, and each course feels as if python programming is tacked–on or isn’t taught comprehensively. For my research, python is essential, and I have a lot of confusion as to why the major is structured in this manner with respect to python.

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 would say requiring students to do research for credit. You need field experience to really gain an understanding of what the field is, as it is very new and still growing. It would be great to have hackathons or events geared towards comp bio students.
• I would have liked coding classes to be more major specific, or have options for coding assignments to relate to comp bio applications.
• Computational biology does not seem well supported in most places, so honestly any additional resources such as people to talk to in the field, and earlier/better teachings of what jobs computational biology is good for. There are many options with the degree, but I wasn’t sure about most of them until toward the end of my undergraduate career
• I would integrate more project–based work into the curriculum so students can gain first–hand experience through experiential learning. I think it could also be good to do more partner programming with the Dept of CSB, graduate–level programs we offer at Pitt, or invite presenters from industry to familiarize undergrads with the various paths they could pursue with computational biology. For example, I know D E Shaw did a talk at CMU some weeks ago –– it would be nice to have these sorts of events available to undergrads as well so we can learn more about the field in academia and industry.
• More applications to real industry use of computational biology methods in courses.
• I would want to use more software relating to the field.
• earlier talks about graduate school preparation. within the first or second year to give students time to find research / mentor opportunities. Talks about what you can do with your degree
• More resources outside the classroom would be helpful. An increase in research opportunities, relevant workshops, and industry connections in things like career fairs would be a good place to start, as well as an increase in course offerings.
• Not sure
• More integrative classes where students can see the practical relevance of computational biology techniques. I can create data visualizations and do rudimentary stuff with unix, but I still don’t have an idea of what I can do with the major. Additionally, we take a lot of intensive computer science courses, but I have not used the knowledge I’ve gained from them in a biologically relevant way. I would like to see more integration of the mandatory CS courses with an application to biological research.
• I would like more mentors who are knowledgeable about the field of computational biology such as Dr. Maldonado to be readily available. I also would like more computational biology courses and less cs courses that I feel do not help me.
• I think that more coding prerequisites for comp bio classes would be good so that the comp bio classes themselves can use coding and aptly prepare students to apply computational methods to topics in biology. Additionally, many students are unaware of the preparation they would need to pursue a comp bio career, like the research they would need to undertake, how to prepare for interviews, the extracurriculars they should be doing like preparing a portfolio or doing their own projects, etc. I am a pre–med student and at Pitt what we need to do to apply to med school is very well outlined for us so everyone knows exactly the things they should be doing as an undergrad and that has prepared me very well, but I don’t think I would be prepared to enter industry in comp bio. I do now understand that most undergrads need a PhD before entering industry in comp bio, so that should also be advertised to students.
• As I previously stated, I think more computational biology specific courses that incorporate practical applications would be beneficial to bridge the gap between the core courses we are required to take.
• Writing a paper has been eye opening, but I would’ve preferred something more related to what you would find yourself doing in a comp bio job.
• More outside resources available to students within the major, but also a refined curriculum and major progression.
• More research opportunities, more practical classes, more comp bio focused python classes, batch programming classes, etc. The department is basically just Maldonado and Durrant, which is insane because this field is quite literally exploding right now. Get it together and follow the trends. Hire more people, use the school of medicine to help you set up the classes and prerequisites.
• More resources on pursuing graduate schools for computational biology and related fields.

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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• I like the way you used PowerPoint slides to give a brief overview of the topic, but didn’t base the entire class around it, giving time for discussion, both individual and group activities, and questions, which I think enhanced my learning as a student.

• I believe you have done a great job teaching this course, as I felt safe to ask questions and I was stimulated intellectually every time I came into class. At times waiting for your grades would be frustrating, and sometimes feedback was confusing. But I would just ask to you to clarify and you have been fair with deadlines. I do believe that you would be great for the comp bio teaching mission as you have already given so much diverse experience to students in this class and the actual comp bio class that you teach. You are very knowledgeable in the field, and you are very driven and passionate about the subject. You wold be great as teaching faculty, the bio department could really use someone like you.

• Dr. Maldonado has been the most helpful and supportive professor I’ve had at Pitt. Most of the courses I’ve taken feel disconnected from anything outside of a classroom environment and haven’t actually prepared me for how I can use the information I’ve gained. This class was the exact opposite: everything we did made the concept of comp bio more concrete to me. I think that Alex would be a great addition to the computational biology department at Pitt due to his passion for teaching and his ability to conceptualize complicated topics for undergrad students.

• Alex is by far the best instructor I have had in my time here at Pitt. He is extremely knowledgeable about his field and has given me a clearer idea of what I’ve been studying than anyone else in the computational biology department. He was always open and responsive to questions, great at explaining, and it felt like he cared for us and our needs as a class. This man is too good for you. Please just give him the job.

• Expectations for assignments are always very clear, and Alex has been willing to meet students where we are if there is a mismatch in what he expects and what we can deliver at the moment. Alex’s feedback is always very thoughtful and thorough, and he engages with students often to discuss what is/isn’t working about how he is teaching the class. He has been very flexible and has prioritized student feedback in order to meet both his teaching goals and provide what we are looking for from the class. Alex has cultivated a class environment which is comfortable and encourages discussion and collaboration. This allows students to freely express if we have concerns about any assignment or if we wish to take the class is a specific direction (for example, we are allowed to discuss deadlines and decide what kinds of papers we would like to learn more about). Alex has also made efforts to bridge the gap between the minimal coursework on computational biology methods most of us had prior to this course (earlier sections of 1540 did not prepare us well for the CADD topics we’ve been discussing in this course, and many of us have not yet taken our higher–level computational biology course). This has been largely by giving pre–lectures on a paper’s topic so that we have a foundational understanding before reading the article and encouraging pre–lecture assignments to skim the paper.

• I sincerely appreciate the effort and dedication you put into this course. Your feedback was thorough, and I gained valuable insights into academic writing. I found your teaching approach effective, particularly your method of selecting key papers, breaking them into components, and encouraging us to work in groups. This structure deepened our understanding of each stage of the research process and helped us connect these elements to the broader context and incorporate them into our writing assignments.

  However, I wanted to share a constructive observation regarding professionalism. As computational biology is a small cohort program, I noticed that your interactions with a few students and UTAs occasionally appeared more relaxed or familiar compared to others. While your jokes and efforts to build rapport were appreciated and reflected your genuine care for the cohort, ensuring that all students feel equally engaged and supported is important for fostering a fully inclusive and professional learning environment.

  Additionally, I observed instances where specific faculty members in the biological sciences department were mentioned in class. While I understand these comments were made with genuine concern for the program and its students, such mentions could raise questions about professional boundaries. As an educator, facilitator, and future career advisor, I believe maintaining a focus on education and fostering a neutral, supportive atmosphere is essential. This professionalism complements the emphasis on research, teaching efficacy, and competence, ensuring students are supported in both their academic and professional growth.

  I hope this feedback is helpful as you continue to refine your teaching practices and pursue a teaching faculty position in computational biology. Your passion for the subject and dedication to student success are evident, and I believe your contributions could greatly benefit the department.

• It is clear that Dr. Maldonado is very passionate and knowledgeable about the field of computational biology, and I think this makes him a great fit for the department. However, I do believe his standards for his students’ understanding and capability of writing scientific papers are simply too high. The classes before his do not prepare us for the graduate level of writing he seems to expect. I encourage him to consider this in his future teaching goals.

• I found you to be a very effective instructor in this course. I believe that the computational biology program here should be expanded with more staff and elective courses, more people knowledgeable in the field like you should be present in the department.

• I think you did a great job teaching this class. It is obvious that you know what you are talking about, and your experience within computational biology was evident with your explanations of tough concepts. I feel like you really pushed our class to learn about the current tools in the field, like machine learning and molecular modeling, and you were readily available to answer the tough questions that came with these complicated concepts. I think we need more classes that take a contemporary approach to computational biology, with less repeated lectures and more investigation into the current state of the field.

• Alex was excellent at providing useful feedback on assignments, especially focusing on areas that have been completely overlooked by the rest of the computational biology program, like honing scientific writing and presenting skills (essential real–world skills). However, he could be disorganized and the class could benefit from more structure.

• I feel like you are a good instructor that doesn’t judge their students. I felt like no question was a dumb question and I felt safe to talk to you about any concerns.

• Alex would be a good contribution to the faculty for computational biology because he has the practical expertise that other professors lack. This was his second time teaching BIOSC 1630 so there is room for improvement as an instructor in terms of returning assignments in a timely manner and assessing what students have been taught. Overall though, I think he would be beneficial as a faculty member.

• Dr. Maldonado really does want to help his students and he is very approachable. He is knowledgable about the computational biology field and I only felt like I was learning about this major after speaking to him and taking his class. In class discussions are comprised of relevant topics to current research and industry and I have found myself talking about the topics Dr. Maldonado discusses outside of class or even seeing them in other classes. I think he is an excellent addition to this department and would assist many computational biology majors in the future with their careers and future goals if he is offered a teaching faculty position.

• I think that Alex is very knowledgeable about the field of comp bio in a way that none of my other professors at Pitt are. Despite the challenges of teaching novel concepts within a relatively new major, he is very adaptable and understanding. He takes student feedback, but also understands where he must stand firm in order to maintain the content of the course. Even though the workload of the course was not extreme, I felt that every activity and every assignment I turned in taught me something.

• I believe that you are a knowledgeable, dedicated, and engaging professor. I gained so much knowledge from you and this course that I would not have had without all your guidance. I not only learned key skills such as reading, writing, and presenting scientific research, but I also learned so much about the field as a whole. I decided that I wanted to pursue a PhD in Computational Biology after you shared your own experiences and insight in the field with the class. You also created environment where students felt safe to ask questions not only about the course, but also about the computational biology and research field and our own career ambitions. You also made sure to listen to your students and heed feedback that not many professors I have encountered do. You also simplified and explain complex topics, which greatly enriched my understanding. Having a professor like you gave me immeasurable understanding and knowledge in this field that I was new to.

• You were not easy to reach over email.

• I think you did an extremely good job of being available to students and answering questions. You also did so in a way that made you extremely approachable, which made it much easier for me to learn. One of the standout qualities was the thoughtful and detailed feedback you provided for all our assignments. Your feedback not only helped me improve my work, but also helped direct my research, which deepened by understanding of the material. Whether through examples, walkthroughs, or addressing questions patiently, you ensured that everyone in the class could follow and understand the material. You also (in my opinion accurately) anticipated areas where students might struggle and proactively clarified those points, making the learning process much smoother and more engaging. The way you were able to break down complicated topics was truly impressive. Also, you went above and beyond by discussing career paths, sharing insights about opportunities in the field, and providing guidance tailored to our individual goals. I truly felt that you were invested in our success, both inside and outside of the classroom. Your ability to communicate complex concepts clearly, your dedication to student success, and your enthusiasm for the field feels like the perfect contribution to the department’s teaching mission, and I strongly believe you would make a vital contribution to the academic and professional development of students in the program.

• Dr. Maldonado is fair, understanding, and knowledgable, and is fighting a hard fight to teach undergrad students useful techniques, especially since the prerequisites for the comp bio classes DO NOT AT ALL set you up for success in the later classes. He knows what needs to be done to make this program insanely competitive and important at Pitt.

• I found that professor Maldonado was unique in his specific feedback––he gave deliberate and intentional feedback on class presentations and on our assignments, and for me his feedback was more in–depth than most professors I have had here at Pitt. This feedback was some of the most rigorous and specific feedback I have received at Pitt, and I feel that this greatly improved my skills, especially in effectively analyzing papers and in academic writing. He also was very deliberate about structuring this course, and I appreciated how he focused on developing our skills in effectively understanding and evaluating information in scientific articles, presenting that information, and also performing academic writing that synthesizes based on information found in papers. I haven’t really had enough guidance on this front here at Pitt, and I feel that my skills in these areas have significantly improved as a result of this course. From these things, I get the impression that professor Maldonado cares greatly about improving the skills and abilities of his students, and has a good focus for what is important to develop in the field of computational biology. Furthermore, he spoke at length many times on the current trends in computational biology research, and given our discussions I feel that I have a more complete handle on the direction that the field is taking.

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

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• As stated above, I feel that some more time could be given to finding the specific perspective that will inform the term paper.
• I’ve enjoyed every aspect of my major, as it allowed flexibility for medical school. But if someone were not going into medical school and wanted to enter the industry from the major, they would not be competitive for jobs. This major requires you to go to grad school if healthcare or some other path is not your path.
• Since it is an underdeveloped field, it is tough to find opportunities in specfic areas and niches. I am still discovering some of the more practical research applications of my work, but given the many different amounts of subfields, I never had an opporunity to explore. It would be nice to have a more central “comp bio” department that is not split between DSAS and SCI, since half of the opportunities and things available to me are in a different school. I would be able to focus on my major more early on with a clearer vision.
• Coursework integrating biology and computer science foundations did not come until the very end of my time here. If I didn’t join a lab, I likely would not have known which direction I wanted to take my computational biology work after graduating. I think this was primarily an issue with the way 1540 was taught, as there was minimal overlap between what we were learning in class and what I was doing in my lab (computational structural biology projects). While I don’t expect a full understanding of how the methods I use in lab work, I do wish I had been introduced to them before utilizing them in lab and gotten at least a general understanding of what they do and how to apply/interpret their results.
• I believe the computational biology major is adequately challenging. I wish the option of computational biology students completing the computer science minor was decided and communicated to students much earlier on. Due to the change being made during my junior year, I was not able to fit in the needed coursework during my remaining time at Pitt.
• The aspect most challenging was some of the general classes such as chemistry.
• the computer science side is much more challenging than the biology side, and I feel like there are more resources for biology help. Alex was always really kind about explaining concepts I didn’t understand (when maybe I should have) and I think we need more professors who have worked in computational biology to bridge the gap in understanding
• The most challenging part has definitely been a lack of available resources and relevant course content in the program, as laid out previously.
• The presentations were hard for me, I felt like I didn’t know enough.
• The classes do not seem thought out, and the lesson plans are extremely disorganized. This is what I’ve noticed from the three computational biology courses I have taken so far.
• The computer science aspects have been challenging as well as the individual concepts in the classes. I think they could be improved by keeping the current computational biology course as is and adding more comp bio courses that are based off of that course.
• I think many people entering the comp bio major at Pitt have no previous programming experience, and that can make it difficult, because coding is so different from any other skill we learn in college. That was the most difficult part for me. I think a better up–front understanding about how much programming this major requires, as well as resources for students to improve their programming skills, will be very helpful. Especially problem–solving and debugging help, so that students know how to solve problems they do not know the answers to.
• I think the most challenging part of the major is taking difficult courses in biology and computer science but having too few courses that are able to bridge the two subjects and give us practical applications to our future careers.
• A lot of the jargon can get complex, especially when reading a research article, but I feel that you did a very good job of breaking that own.
• The lack of resources, advice, and opportunities

What are your career goals after graduation?

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• Medical School and maybe work in biotech afterward.
• I’m very undecided between med school or some other health career path.
• My main goal right now is to do a post–bac or fellowship program, and enroll in a PhD program further into the future. After that, I hope to continue research and potentially teach.
• Graduate programs in computational biology/bioinformatics/biotech, possibly into industry
• Graduate school
• Attending medical school to become a physician.
• I want to attend grad school
• I am going to medical school
• After graduation, I plan to start a job in industry and potentially get a masters degree.
• Masters
• Pursue a PhD in computational biology or bioinformatics and work in industry or an NGO.
• My career goals are to go into medicine. However, I hope to do computational neuroscience research hopefully or research related to my major in medical school.
• I plan to apply to medical school and become a physician, eventually splitting my time between clinical practice and research.
• I would like to pursue a PhD in computational biology and eventually work in cancer drug research and development.
• Grad school
• Comp Bio research in the school of medicine.
• Graduate school and research in academia

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

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• Knowledgable, Kind, Patient
• Someone who has experience in computational research, can break down topics for student understanding, and is adaptable with the evolution of the field.
• Being open and responsive to questions, great at explaining, and it caring for the needs of a class.
• Strong understanding of the field, flexible, and approachable
• Being interested, up–to–date, and knowledgable in the field of computational biology.
• Being supportive, knowledgeable
• Understand and can explain computational biology. Ideally have research / career experience working in computational biology or applying computation to their biological research. Have a good grasp on where the field is now, and where they think it is heading
• Computational biology is a field that encompasses lots of things, and I think it is important for an instructor to be knowledgable in many of these. Many instructors are only knowledgable in the field of their specific research, which leaves students with an incomplete picture of the field and what opportunities are available to then after they graduate.
• Approachability
• Someone who has both experimental and computational research expertise, and is able to effectively integrate them and show students how both types of research come together through computational biology.
• An instructor must know current industry and what topics are relevant right now. They should help inform their students what skill sets they need to be successful for a career in computational biology instead of simply teaching a class. They also need to be approachable and willing to talk with their students and make recommendations based on the students’ career path.
• Adaptable, understanding, knowledgeable about the field, willing to continuously make changes to curriculum because the field is constantly evolving. Cares about students’ well–being and flexible with deadlines because the course material is difficult and flexible deadlines can allow for a better final product.
• There are numerous essential qualities of a successful instructor for computational biology courses. It is important to be able to simplify and explain complex topics in this field and give students real–world applications. Additionally, it is necessary to listen to students and create an environment where students feel comfortable seeking help. An instructor who also provides guidance in the field as a whole, with tools that we can apply in the future.
• Patience, persistence, compassion, enthusiasm
• Understanding of students knowledge, understanding of the current field, and understanding of how to merge these two to effectively teach students in a efficient way.
• In a fast–moving field like computational biology, I feel that professors who prioritize a forward–facing approach to teaching topics are essential.