Integrative modeling meets deep learning: Recent advances in modeling protein assemblies

B Shor, D Schneidman-Duhovny - Current Opinion in Structural Biology, 2024 - Elsevier
Recent progress in protein structure prediction based on deep learning revolutionized the
field of Structural Biology. Beyond single proteins, it also enabled high-throughput prediction …

Fast Inference Using Automatic Differentiation and Neural Transport in Astroparticle Physics

DWP Amaral, S Liang, J Qin, C Tunnell - arXiv preprint arXiv:2405.14932, 2024 - arxiv.org
Multi-dimensional parameter spaces are commonly encountered in astroparticle physics
theories that attempt to capture novel phenomena. However, they often possess complicated …

Recent methods from statistical inference and machine learning to improve integrative modeling of macromolecular assemblies

S Arvindekar, K Majila, S Viswanath - arXiv preprint arXiv:2401.17894, 2024 - arxiv.org
Integrative modeling of macromolecular assemblies allows for structural characterization of
large assemblies that are recalcitrant to direct experimental observation. A Bayesian …

Frontiers in integrative structural biology: modeling disordered proteins and utilizing in situ data

K Majila, S Arvindekar, M Jindal… - arXiv preprint arXiv …, 2024 - arxiv.org
Integrative modeling enables structure determination for large macromolecular assemblies
by combining data from multiple sources of experiment data with theoretical and …

A deep learning method for predicting interactions for intrinsically disordered regions of proteins

K Majila, V Ullanat, S Viswanath - bioRxiv, 2024 - biorxiv.org
Intrinsically disordered proteins or regions (IDPs or IDRs) exist as ensembles of
conformations in the monomeric state and can adopt diverse binding modes, making their …