CDB 560 – Quantitative Cell Biology

Description: Biophysical and biochemical techniques, computational analysis, and bioinformatics have become essential components of modern research in molecular and cellular biology. The cutting-edge techniques let us observe biology at every size scale with unprecedented resolution; mathematical modeling and statistical analyses reveal how the laws of chemistry and physics shape biology; and bioinformatics distills vast troves of data to reveal unexpected correlations and generate new hypotheses. This course will introduce first-year PhD students to the basic theory and practice of these aspects of quantitative cell biology. 

The course incorporates six modules that exemplify how key advances in molecular and cellular biology depend critically on quantitative methods and reasoning:

  1. Quantitative analysis of biological interactions (leads: Ajit Joglekar, David Sept)
  2. Protein structure (lead: Melanie Ohi)
  3. Molecular basis of cytoskeletal organization (leads: Kristen Verhey, David Sept)
  4. Membrane biology (lead: Sarah Veatch)
  5. Signaling, cell fate, and patterning (lead: Idse Heemskerk)
  6. Hypothesis generation using bioinformatic analyses (leads: Mara Duncan, Craig Johnson)

Organization: Two class sessions, each 2-hours long, will be held each week. Each module will span two weeks and will integrate the following elements: (a) theory and foundational knowledge, (b) experimental design and techniques, (c) hands-on quantitative data analysis, and (d) statistical inference. The emphasis will be on in-class discussions and group problem-solving exercises designed to build mastery of basic concepts, methods, reasoning, and computational skills for modern cell biology. The course will use Python scripts for data analysis and will include an introduction to Python (no prior training necessary). Students are expected to bring their own laptop computers to every class.

CDB560 (old) – Principles and practice of quantitative Fluorescence Microscopy