Lectures related to Protein function prediction

Machine-learned force fields for molecular simulation

Explores machine-learned force fields for accurate molecular simulations and the solution of the electronic Schrödinger equation.

Predicting completion time: Activity Progress

Covers the prediction of completion time in activities based on progress data.

Hidden Markov Models (HMM): Theory

Covers Hidden Markov Models (HMM) for modeling time series data and decoding using the Viterbi Algorithm.

Quantifying Randomness and Information in Biological Data

Explores entropy, randomness, and information quantification in biological data analysis, including neuroscience and protein structure prediction.

Protein Functions and Interactions: Sequence Analysis

Explores predicting protein structure from sequence data and inferring interaction partners through Direct Coupling Analysis and the Iterative Pairing Algorithm.

Entity Disambiguation and Link Prediction

Explores entity disambiguation, linking text to knowledge bases, and link prediction in knowledge graphs with examples from Wikipedia.

Quantitative Proteome Profiling: Chemical Target Identification

Explores quantitative proteome profiling for drug target identification through activity-based protein profiling and advanced mass spectrometry techniques.

Proteomics Profiling Methods

Explores proteomics profiling methods, including ABPP, MS approaches, and quantitative target identification using SILAC and TMT labeling.

Proteomics: Post-Translational Modifications and Interactions

Explores proteomics for post-translational modifications and protein interactions.

Single Molecule Studies: Hsp90 Chaperone

Explores single-molecule studies of the Hsp90 chaperone and protein function using optical tweezers.

Protein Function Regulation: Degradation Mechanisms

Covers the mechanisms of protein degradation, including the roles of the proteasome and autophagy in regulating protein function.

Kernel Methods: Recap and Applications

Covers polynomial feature expansion, kernel methods, data representations, normalization, and handling imbalanced data in machine learning.

Activity-based Protein Profiling: Druggable Sites Identification

Explores Activity-based Protein Profiling for druggable site identification and strategies to minimize off-target reactivity of covalent inhibitors.

Protein Structure Prediction: Alphafold2

Explores the revolutionary Alphafold2 for protein structure prediction and its impact on bioinformatics and protein folding biology.

Protein Structure Prediction

Explores predicting protein structure from sequence data using maximum entropy modeling and discusses recent advancements in protein structure prediction.

Protein-Protein Interaction Networks

Explores protein-protein interaction networks, binding importance, experimental approaches, drug target identification, and network construction.

Protein Expression and Purification

Covers the process of expressing and purifying proteins, including the importance of studying protein function, folding, interactions, sequence, and structure.

Link Prediction: Missing Edges and Probabilistic Methods Log in to Mediaspace to watch this video

Explores link prediction in networks, covering missing edges, probabilistic methods, and causal inference challenges.

Metabolic Engineering: Systems Biology and Tools Log in to Mediaspace to watch this video

Explores systems biology of metabolism, genome-scale models, and metabolic engineering applications.

Linear Regression: Estimation and Prediction Log in to Mediaspace to watch this video

Covers the basics of linear regression, focusing on estimation and prediction.