ES_APPM 395-0: Modeling Experiments & Data (Also BioSci 354-0-1)

Quarter Offered

Fall : TTh 3:30-4:50 ; Mani


The Era of Quantitative Biology

We are at the beginning of the quantitative era of biology. While the molecular era has endowed us with an experimental paradigm and a molecular parts list for many living systems, we are still far from understanding how a cell computes or how an organism puts itself together. High resolution imaging and sequencing are technologies that give access to dynamics and possess the ability to drive new discoveries. We must learn to quantify, analyze, model, and interpret them.

Course Goals

High-resolution, high-throughput, and dynamic imaging and sequencing data is the substrate of modern biological and biomedical study in labs and in industry. Every module is centered around a biological case-study that comes with a dataset. The goal is to learn how to computational work with, analyze, and make sense of the dataset. This is what we will teach you.

You will learn how to:

  • Learn how to code in python
  • Load and navigate through datasets on your laptop
  • Analyze data based on fundamental principles of mathematics, statistics, and physics
  • Present your analyses with clarity and precision


  1. Coin Flipping and Motion
  2. States and Weights
  3. Hypotheses and Statistics
  4. Information Theory and Stochastics
  5. Transfer Functions and Variance Analysis
  6. Networks and Dynamical Systems
  7. Time-Series Analysis
  8. Analysis of High-Dimensional Data
  9. Images and Analysis
  10. Sequences and Analysis
  • Each module is designed around a key mathematical, physical, or statistical concept and a biological case-study.
  • Assignments at the end of each module will involve visiting the core concepts introduced during the past week, further development of coding skills, and the analysis of a published biological dataset.
  • An in-class final will test the core concepts of each module


  1. Interest in programming. Prior experience will be beneficial but isn't required.
  2. Prior experience with Calculus, linear algebra, and differential equations will be useful but not required.
  3. An interest in doing a new kind of biology is required.

Write to if you have any questions or visit the course website.