Entropy in Neuroscience and Ecology

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Lecture: Shannon

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Mutual Information in Biological Data

Explores mutual information in biological data, emphasizing its role in quantifying statistical dependence and analyzing protein sequences.

Data Compression and Entropy Definition

Explores the concept of entropy as the average number of questions needed to guess a randomly chosen letter in a sequence, emphasizing its enduring relevance in information theory.

Source Coding Theorems: Entropy and Source Models

Covers source coding theorems, entropy, and various source models in information theory.

Biological Randomness and Data Analysis

Explores randomness in biology, covering thermal fluctuations, random walks, and data analysis techniques.

Protein Structure Prediction: AlphaFold Evolution and OpenFold Insights

Explores the evolution of protein structure prediction with AlphaFold models and introduces OpenFold insights.

Thermodynamic Identity: Entropy and Energy

Explores the thermodynamic identity, entropy-temperature relationship, and pressure definition, illustrating key principles with practical examples.

Second Principle: Entropy

Explores the second principle of thermodynamics, emphasizing entropy's role in system evolution and equilibrium.

Energy Minimization in Biological Systems: Equilibrium Models

Covers energy minimization models in biological systems, focusing on equilibrium and the roles of entropy and hydrophobicity.

Entropy and KL Divergence

Explores entropy, KL divergence, and maximum entropy principle in probability models for data science.