q-bio Summer School and Conference, 2022

UQ-Bio Testimonials

Below are some of the many anonymous comments submitted by students of the 2021 UQ-Bio Summer School.

  • “The google colab notebooks were especially impressive. They were well-prepared, and very detailed. I can see that they were definitely made to make it easy for first-time students to understand.”

  • “I really liked the diversity of the UQ-Bio summer school program”

  • “It was really easy to get in touch with our project manager in order to clarify ideas, or ask for guidance! The challenge projects were really helpful for properly understanding concepts presented on tutorials and lectures. The material (overall) was delivered in a consistent fashion, and I strongly appreciate the huge effort in putting together so many different topics under the same framework. The opportunity to use several state of the art methods, as well as tools developed by the organizers, is truly encouraging for learning!”

  • “In my view, the strongest aspect of the program was that material that was covered as well as the speakers who gave talks on the material. Even though I come from a Bioengineering field (that is not quantitative biology related), I really liked the topics that were covered program where I could learn about the latest research and tools that can be utilized to study single cell biology dynamics…I enjoyed each and every talk…, as well as the questions from students and the speakers themselves. I also liked the fact that we could ask questions during the talk, and test out different ideas on the fly during tutorial sessions – these were all informative and helpful. Last but not least, I must thank the Learning Assistants (especially Will Raymond) who spent a great deal of time explaining to our group … nuances of the code, and answered questioned related to code and course material. Other things which were also important was the use of slack, creating a zoom link for team discussion, and posting of the zoom sessions – these were absolutely necessary for me to revisit and listen the material again, as well as coordinate conversations between our team members.”

  • “I loved the SSA lecture – it was very clear and was the first time I had seen math used to describe gene regulation. Because I enjoyed the SSA so much, the FSP lectures were also great, as they seemed like an extension of SSA.”

  • “Stochastic simulations and the chemical master equation were the two modules of most use to me. They were very exciting, very well taught, and had very clear applicability to biological research. I am super psyched to apply the concepts from these modules to my own research in the future. “

  • [What was most important to me was] “the discussion panel in which we discussed how to know the right graduate program, because I have been working on this important decision and the tips given are super important”

  • “all the invited guest lectures are fabulous”

  • [What was most important to me was] “solving master equation and inference. I would like to incorporate these theories into my future research at grad school. My lab is focusing on cell dynamics, which is highly relevant.”

  • “the image processing was very interesting”

  • [What was most important to me was] “Imaging segmentation and stochastic simulation CMEs: I found direct application to what I see in my classes and research.”

  • “Mary Dunlop’s lecture (June 8) and the June 22 Career Panel were most important to me because they both discussed the idea of broader impact. This helped me to think about what I wanted to do with my work and how I want to reach out to my community with it.”

  • “All of the tutorials were great and very helpful.”

  • “I found basic statistics, Stochastic simulation and FSP modules helpful as their material and discussion enhanced my technical knowledge and cleared many of my doubts on role of stochasticity in modeling regulatory networks.”

  • “From a research perspective each lecture and tutorial session was important. For example, the challenges of parameter estimation became very clear during the final weeks, and why we need to spend more time on this area of research. … From a personal point of view, the career discussion panel was the best! The career discussion panel helped me understand why some students struggle with graduate school … The career discussion talks on equity and bias were both education and necessary, as we strive towards creating a welcoming community. Lastly, the thoughts on career choices after post-graduate school were also helpful.”

  • “I really like the order in which lectures and tutorials are given to the students. They build up on each other and are, in my opinion, taught at a very good pace (not too fast or slow).”

  • “Some Career Panels discussed ideas I never even considered before, and the panel members presented some really unique thinking methods. I found it very intriguing to learn from them. They also discussed some ways to develop good habits, which I think is very helpful for students like me to incorporate into their lives.”

  • “Stochasticity is indispensable in biological system, and the extent of its incorporation depends on the process under study. An experimental data can be explained by accounting stochasticity at different levels, however, which model capture the underlying biological mechanism must be figured out. While tutorials in the course taught me SSA and FSP, the guest lectures gave enough exposure to ways to find the right stochastic model that have predictive capability also.”

  • “Materials are very detailed, clear and well explained. Very useful for beginners and researchers both.”

  • “The last module (Single-Cell Inference) was the most interesting. It’s the most thought-provoking topic as one must combine ideas from almost all of the other modules in order to start grasping its far-reaching applications.”

  • “The opportunity to grow as a collaborative coder was the best aspect of the project to me. Project 2 was put together extremely well, with LA’s making themselves readily available to help us and providing us with weekly project colab notebooks that gave us a starting point to jump off of. This really promoted a collaborative environment between me and my teammates, and I got to practice what it is like to code in an environment where I am not the only one reading and writing my work.”

  • “The collaborative teamwork of the course projects were great, it allowed me to learn from others and not afraid to ask for help within our small groups.”

  • “I liked the fact that everyone in my group came from diverse backgrounds. I thought it was cool how they may have a better understanding of certain concepts”

  • “Slack Channel discussions, Prof Munsky’s inputs throughout the lectures were very crucial for my understanding and the website made everything very easy to navigate.”

  • “A challenging-yet-clear application for the topics explored during most of the tutorials (and lectures, of course). The great opportunity of working with real-data experiments, and using state-of-the-art methods co-developed by the organizers.”

  • “The best aspects of the course projects were the LAs and the ability to apply the information learned that week to an actually relevant problem to practice with. The LAs were very nice and they helped a lot with figuring out components of the project. I also really enjoyed that the course project had actual biological information that we were practicing with, instead of a typical practice problem one would obtain in a normal classroom setting.”

  • “I was an LA so it was great to see the students working together and seeing the unique approaches they took to solving problems.”

  • “Good lecturers, good skills to pick up, overall interesting and nerdy”

  • “This was a well prepared, meaningful and purposeful program that quantitative biologists would benefit from.”

  • “I learned a ton from the tutorials, and was fascinated by all the invited speakers.”

  • “It is super relevant to students studying Chemical and Biological Engineering at CSU. Many of those students are excited about microbiology, with classes such as reactor design discussing the engineering of fermenting bacteria at a large scale. The engineering aspect of the degree also makes this program VERY accessible mathematically. I think that every CBE student should know about this program; the degree is the perfect mix of interdisciplinary subjects to prepare a student for this course.”

  • “I think it is a great program to practice and exercise computational biology and an experience that can be easily integrated to your own research interests.”

  • “It is a very good platform to learn and to share.”

  • “free and excellent lectures”

  • “It is a very well paced introductory course to quantitive biology. Moreover, these modeling theories are put to practice by Python tutorials, which is important because many quant bio classes do not teach implementation. I also love the career panel discussion because it provides different perspectives, both from professors and grad students, that I feel deeply related or that I look up to.”

  • “it was very interesting and very well organized”

  • “All the information necessary for quantitative application in biology being taught and practiced in one place.”

  • “I felt like the information being presented was very relevant and that just being exposed to these concepts was very helpful. I felt like I learned how to think about problems computationally much better.”

  • “I believe it is a great opportunity to learn about interdisciplinary research and also interact with other students.”

  • “The program is a great place for students to learn about bioinformatics tools.”

  • “Depending on research field, some of the topic could be very inspiring and useful, but in general, participant get the chances to learn state of the art algorithm and research method for well-known scientists”

  • “It is a great opportunity to learn to code in Python and to combine image processing and modeling in one language.”

  • “This was a great learning experience.”

  • “As each module in itself was a research area of study, this program will provide enough opportunity to make a well informed choice for their research area/career.”

  • “If one really wants to get computational insights and a powerful kick-start in this field, then it’s a wonderful experience!”

  • “I found this program to be very helpful, and it provided a really good place to learn information I hadn’t learned in my coursework.”

  • “Again it was fascinating and well structured, also very accommodating of students who may not be able to be a full participant but still want exposure to the material.”

  • “It is a wonderful introduction to the new techniques that are becoming increasingly important in the field (for the novice) and fantastic way of learning of new topics (for those neither much experience with the tools)”

  • “it is very formative”

  • “I was very helpful in learning python and the topics covered. I also liked how it covered the gap between the biology and quantitative analysis.”

  • “It was interactive and the materials available for self study.”

  • “I hope to be able to collaborate with people I met in UQBIO on research projects, continue networking for job or study opportunities”

  • “I hope remain in contact with some of my group members, my LA, and others through slack to continue networking and learning from each other.”

  • “I would like to share and discuss about the mathematical model used to capture stochasticity. Also, I would like to take part in Diversity, Inclusion and Equity actions/activities of the uq-bio.”