Computational Protein Design

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Protein Design: Structure and Function

Covers protein design fundamentals, including secondary structures, amino acid propensity, loops, and computational methods.

Protein Structure: General Principles

Explores protein structures, folding principles, and sequence determinants, emphasizing the diverse three-dimensional structures proteins can adopt.

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Protein Folding Dynamics

Explores protein folding dynamics, chaperones, ATP hydrolysis, and DNA folding intricacies within the nucleus.

Potts Model: Introduction

Introduces the Potts model, a generalization of the Ising model used in statistical mechanics to study phase transitions.

Protein Interaction Fingerprinting with Geometric Deep Learning

Explores deciphering protein interaction fingerprints using geometric deep learning and the challenges in computational protein-protein interaction design.

Magnetic Moments and Spin

Explores magnetic moments, spin, and quantum descriptions using Pauli matrices and Stern-Gerlach experiments.

Scaling & Renormalization in Statistical Mechanics

Explores scaling and renormalization in statistical mechanics, emphasizing critical points and invariant properties.

Thermodynamics: Exploring Thermodynamic Potentials and Equilibrium States

Covers thermodynamic potentials and their role in system equilibrium with reservoirs.