Physical Biology & Quantitative Biology
Count, model, predict, measure, and revise: a video-first introduction to gene regulation, regulatory genomics, biological fidelity, active matter, and quantitative viral ecology.
2 modules · 6 lessons · 0.7h · mastery threshold 80
Watch videos free — no sign-inBackground for Research in the Rob Phillips Physical Biology Laboratory This independent educational primer introduces scientific concepts relevant to research themes in the Rob Phillips Physical Biology Laboratory at the California Institute of Technology. It is not an official Caltech or Rob Phillips Laboratory course and does not imply endorsement or affiliation. For ambitious high-school students and early undergraduates with high-school biology and algebra; probability is helpful. Approximately 40–45 minutes including six video-first lessons and assessments. Mastery-only certificate eligibility at 80%, without a capstone or Research Defense.
Module 1
Counting, minimal models, and sequence-to-expression measurements.
Module 2
Energy, fidelity, collective materials, and viral ecology.
Active matter and molecular motor energy consumption
Identify local energy consumption in active materials.
Binding energy, occupancy, fold-change, and allostery
Connect copy number, binding energy, fold-change, and ligand-dependent allostery.
Biological fidelity, energy expenditure, and error correction
Explain why fidelity requires mechanism-specific coupling and evidence.
Biological numeracy, scale, and order-of-magnitude reasoning
Estimate biological quantities with units and order-of-magnitude reasoning.
Coarse-graining and predictive minimal models
Distinguish a minimal model, a fitted parameter, and a prospective prediction.
Collective microtubule–motor dynamics and emergence
Connect motor interactions to emergent microtubule dynamics and measurements.
Equilibrium versus nonequilibrium biological processes
Distinguish equilibrium discrimination from driven processes.
From measurement to model across biological scales
Apply measurement-to-model reasoning while preserving causal limits.
Information footprints and regulatory-architecture inference
Interpret information footprints without claiming protein identification.
Quantitative viral genomics and bacteriophage ecology
Interpret viral-genomics and phage-ecology observations within their dataset.
Regulatory DNA and massively parallel sequence-to-expression measurement
Explain sequence-to-expression reporter measurements.
Statistical mechanics of transcriptional regulation
Relate statistical weights to occupancy under stated assumptions.