Biophysics Course

Lesson 1 • Scope and History of Biophysics

Traces biophysics from early physical biology to modern molecular imaging. Contextualises the discipline within physics, chemistry, and biology.

Lesson 2 • Electrostatics and Biological Charges

Examines electric forces, potentials, and ionic interactions in aqueous environments. Connects electrostatics to membrane and protein function.

Lesson 3 • Essential Mathematics for Biophysics

Reviews calculus, linear algebra, and probability as applied to biological problems. Provides the quantitative toolkit for all subsequent chapters.

Lesson 4 • Statistical Mechanics and Fluctuations

Introduces Boltzmann statistics and partition functions relevant to molecular biology. Explains how thermal fluctuations drive biological phenomena.

Lesson 1 • Molecular Simulation Approaches

Introduces computational methods for modelling biomolecular structure and dynamics. Bridges theoretical force fields to experimental observables.

Lesson 2 • Covalent and Non-Covalent Interactions

Distinguishes bond types and their energy scales in biological macromolecules. Establishes the hierarchy of forces governing molecular structure.

Lesson 3 • Nucleic Acid Structure and Mechanics

Describes DNA and RNA architecture through base stacking and hydrogen bonding. Links structural properties to replication and transcription mechanics.

Lesson 4 • Protein Structure and Stability

Analyses primary through quaternary protein structure using physical principles. Connects folding thermodynamics to biological function.

Lesson 1 • Fluid Mechanics in Biological Systems

Introduces low Reynolds number fluid dynamics relevant to cells and microorganisms. Applies Stokes drag and Poiseuille flow to biological contexts.

Lesson 2 • Fick's Laws and Diffusion Equations

Applies Fick's first and second laws to concentration gradients in tissues. Solves diffusion equations for biologically relevant geometries.

Lesson 3 • Ion Transport and Membrane Potentials

Covers passive and active ion transport mechanisms and the Nernst equation. Connects electrochemical gradients to membrane potential generation.

Lesson 4 • Brownian Motion and Random Walks

Derives diffusion from microscopic random motion of particles. Establishes the stochastic foundation for all biological transport phenomena.

Lesson 1 • Membrane as an Electrical Capacitor

Models the lipid bilayer as a capacitor and resistor in parallel. Derives the cable equation for signal propagation in neurons.

Lesson 2 • Membrane Mechanics and Curvature

Applies Helfrich elasticity theory to membrane shape and deformation. Links curvature energy to vesicle formation and endocytosis.

Lesson 3 • Patch Clamp Electrophysiology

Covers patch clamp configurations and data acquisition for single-channel recording. Connects experimental noise analysis to channel biophysics.

Lesson 4 • Hodgkin-Huxley Model of Excitability

Derives and simulates the Hodgkin-Huxley equations for action potential generation. Applies gating variable formalism to neuronal excitability.

Lesson 1 • UV-Visible and Infrared Spectroscopy

Applies electronic and vibrational spectroscopy to protein and nucleic acid characterisation. Connects spectral features to secondary structure content.

Lesson 2 • X-Ray and Neutron Scattering Methods

Explains diffraction principles and structure factor calculations for crystallography. Applies small-angle scattering to solution-phase biomolecular analysis.

Lesson 3 • Principles of Light-Matter Interaction

Derives absorption, emission, and scattering from quantum mechanical transitions. Establishes Beer-Lambert law and molar extinction coefficients.

Lesson 4 • Fluorescence Spectroscopy and Microscopy

Covers fluorescence excitation, emission, and quenching in biological applications. Links Förster resonance energy transfer to molecular distance measurement.

Lesson 1 • Single-Molecule Fluorescence Methods

Applies total internal reflection fluorescence and confocal detection to single molecules. Analyses intensity trajectories for conformational dynamics and binding events.

Lesson 2 • Optical Tweezers and Force Spectroscopy

Derives the optical trap potential and calibration methods for force measurement. Applies optical tweezers to protein unfolding and motor stepping experiments.

Lesson 3 • Atomic Force Microscopy in Biology

Covers AFM imaging modes and cantilever force calibration for biological samples. Connects force-distance curves to molecular adhesion and elasticity.

Lesson 4 • Rationale for Single-Molecule Approaches

Contrasts ensemble and single-molecule measurements and their information content. Motivates single-molecule methods for detecting heterogeneity and rare states.

Lesson 1 • Traction Force Microscopy

Measures cell-generated forces on substrates using bead displacement and elasticity theory. Connects traction maps to cytoskeletal tension and migration.

Lesson 2 • Tissue Mechanics and Collective Behaviour

Extends single-cell mechanics to multicellular tissue deformation and jamming transitions. Applies continuum mechanics to epithelial monolayer dynamics.

Lesson 3 • Mechanosensing and Mechanotransduction

Examines how cells detect and convert mechanical stimuli into biochemical signals. Links integrin-mediated adhesion to downstream signalling cascades.

Lesson 4 • Cell Viscoelasticity and Rheology

Models cells as viscoelastic materials using creep and stress relaxation experiments. Applies microrheology techniques to measure intracellular mechanical properties.

Lesson 1 • Biological Oscillators and Clocks

Analyses limit cycle oscillations in repressilator and circadian clock models. Applies Hopf bifurcation theory to oscillator design principles.

Lesson 2 • Bistability and Switch-Like Behaviour

Derives conditions for bistability in genetic toggle switches using nullcline analysis. Connects bistability to cell fate decisions and differentiation.

Lesson 3 • Stochastic Gene Expression

Models intrinsic and extrinsic noise in gene expression using master equations. Connects noise propagation to phenotypic variability in cell populations.

Lesson 4 • Signalling Cascades and Information Theory

Quantifies information transmission in signalling pathways using mutual information. Applies channel capacity concepts to receptor-ligand signalling fidelity.