Covers techniques for mapping protein-protein interactions, including affinity purification, proximity labeling, and co-fractionation, emphasizing their applications in neuroscience.
Explores predicting protein structure from sequence data using maximum entropy modeling and discusses recent advancements in protein structure prediction.
Explores covalent lipid modifications of proteins and their role in protein-membrane interactions, including the biochemistry of membrane proteins and the challenges of studying them.
Explores predicting protein structure from sequence data and inferring interaction partners through Direct Coupling Analysis and the Iterative Pairing Algorithm.
Covers the process of expressing and purifying proteins, including the importance of studying protein function, folding, interactions, sequence, and structure.
Covers proteomics techniques and their applications in neuroscience, focusing on mass spectrometry and the challenges of studying proteins in cellular functions.
Explores protein design challenges, validation through crystallography, evolution of design techniques, and the difference between genetic and protein circuits.
Explores deciphering protein interaction fingerprints using geometric deep learning and the challenges in computational protein-protein interaction design.
