Welcome to Biological Modeling!
Have you ever wondered why zebras have stripes? Have you ever wondered how your cells can quickly react to their environment and perform complex tasks without intelligence? Have you ever wondered why the original SARS coronavirus fizzled out but SARS-CoV-2 has spread like wildfire around the planet? Have you ever wondered how algorithms can be trained to “see” cells as well as a human?
What these questions share is that they can start to be answered by modeling biological systems at multiple “scales” of resolution, from the microscopic to the molecular.
In this free course, we will build models of biological systems that are relatively simple but nevertheless provide us with deep, fascinating insights into how those systems operate.
Course structure and contents
This online course is divided into a prologue and four main modules. Each of the five parts of the course covers a single biological topic (e.g., “Analyzing the structure of the SARS-CoV-2 spike protein”) and introduces all of the modeling topics needed to address that topic from first principles. The modules build on each other, so we suggest covering them in order, although it is possible to complete them out of order.
Each module has a main narrative that can be explored by anyone, including beginner modelers; this main narrative will form our upcoming book. When we need to build a model along the way, we pass our modeling work to “software tutorials” that show how to use high-powered modeling software produced by MMBioS researchers to build biological models. The software tutorials allow users wishing to get their hands dirty with modeling software to build all of the models that we need in this course. This allows for a course that can be explored by both casual and serious biological modeling learners alike.
After building a model in a software tutorial, we will return to the main text and analyze the results of this model. In this way, the text forms a constant interplay between establishing a biological problem, describing how a model work, implementing that model in a software tutorial, and returning to the text to analyze the model and ask our next question, beginning the cycle anew.
Our course contents are found below.
Module 1: Finding motifs in transcription factor networks (with software tutorials featuring MCell and CellBlender)
Module 2: Unpacking E. coli’s genius exploration algorithm (with software tutorials featuring BioNetGen)
Module 4: Training a computer to classify white blood cells (with software tutorials featuring CellOrganizer)
Meet the team
Preorder the book
We are producing a textbook companion to this course, called Biological Modeling: A Short Tour. Its pending publication in spring 2022 was graciously funded by the community at Kickstarter; if you would still like to preorder the book at its introductory price (and receive a complementary E-book), we are continuing to take pre-orders during winter 2022 on Indiegogo.
Course survey and contact form
Please use our anonymous survey so that we can track information about the demographics of our learners.
Whether you loved our course and would like to provide a testimonial, or you’re an instructor interested in adopting this material in your class, or you just want to say hi, then we would love to hear from you. Please use our contact page to get in touch!
This online course is a training and dissemination effort for the National Center for Multiscale Modeling of Biological Systems (MMBioS). It is supported by the National Institutes of Health (grant ID: P41 GM103712).
We would first and foremost like to thank everyone working on MMBioS software; their work allowed this project to come about. Chiefly, thank you to the other members of our training and dissemination team (Alex Ropelewski, Joe Ayoob, and Rozita Laghaei) as well as the head of the MMBioS consortium, Jim Faeder.
We are also very grateful to Wendy Velasquez Ebanks, Julien Gomez, Yanjing Li, Ulani Qi, Aditya Parekh, and Shalini Panthangi, who provided additional work on the course during its conception.
Module 1 was in part inspired by Uri Alon’s research and superlative book An Introduction to Systems Biology, a landmark biological textbook that we strongly recommend if you are interested in a greater discussion of biological network motifs.
Special thanks to Jiayi Shou for the analogy in Module 3 of new protein companies rising like “bamboo shoots after the rain”.
The cover image on Module 4 was created by Keith Chambers.
Finally, the website design was built using Michael Rose’s excellent Minimal Mistakes theme.
You might also enjoy…
If you like this course, then we would suggest some additional resources below.
Additional open educational materials in computational biology and programming
We think you would love some of the other free education projects developed by the project founder. We list these resources below.
Bioinformatics Algorithms: An Active Learning Approach: A best-seller in its field, this textbook has been adopted by over 170 instructors in 40 countries around the world. It has also been used as the basis of the Bioinformatics Specialization on Coursera, which has reached hundreds of thousands of online learners. The first several chapters of the book is available for free on the textbook website.
Rosalind: An open platform for learning bioinformatics independently through problem solving.
Programming for Lovers: An open course in introductory programming aimed at science students. The course is still in development.
MMBioS Training Workshops
If you are a biological modeling researcher and want to learn more about how the software resources presented here can be applied to your work, please check out the workshops organized as part of the MMBioS project to which this course belongs.
Another textbook on biological modeling
A colleague at Carnegie Mellon University, Russell Schwartz, authored a textbook called Biological Modeling and Simulation that you may enjoy. Dr. Schwartz’s book focuses on a different collection of modeling topics than this work.