activity
20192024
most citedOpenProteinSet: Training data for structural biology at scale

15 citations · 32 across the 6 of their papers we have counts for

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Showing q-bio.BMShow all

5 papers · 1 filter

q-bio.BM2024★ 1 cited

QuickBind: A Light-Weight And Interpretable Molecular Docking Model

Wojtek Treyde, Seohyun Chris Kim, Nazim Bouatta +1

Predicting a ligand's bound pose to a target protein is a key component of early-stage computational drug discovery. Recent developments in machine learning methods have focused on…

q-bio.BM2023

Growing ecosystem of deep learning methods for modeling protein$\unicode{x2013}$protein interactions

Julia R. Rogers, Gergő Nikolényi, Mohammed AlQuraishi

Numerous cellular functions rely on protein$\unicode{x2013}$protein interactions. Efforts to comprehensively characterize them remain challenged however by the diversity of molecul…

q-bio.BM2023★ 15 cited

OpenProteinSet: Training data for structural biology at scale

Gustaf Ahdritz, Nazim Bouatta, Sachin Kadyan +7

Multiple sequence alignments (MSAs) of proteins encode rich biological information and have been workhorses in bioinformatic methods for tasks like protein design and protein struc…

q-bio.BM2019★ 6 cited

Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations

Iddo Drori, Darshan Thaker, Arjun Srivatsa +15

Proteins are the major building blocks of life, and actuators of almost all chemical and biophysical events in living organisms. Their native structures in turn enable their biolog…

q-bio.BM2019★ 2 cited

ProteinNet: a standardized data set for machine learning of protein structure

Mohammed AlQuraishi

Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like…