Official repository for the Protriever paper

OMEGA code described in "Scalable and cost-efficient custom gene library assembly from oligopools."

Vina-GPU 2.0 accelerates AutoDock Vina and its related commonly derived docking methods, such as QuickVina 2 and QuickVina-W with GPUs.

Predict multiple protein conformations using sequence clustering and AlphaFold2.

Python for Hamilton liquid handling robots

Protein hallucination and inpainting with RoseTTAFold

DDGScan: an integrated parallel workflow for the in silico point mutation scan of protein

scripts and facilities for in-silico mutagenesis with FoldX

Convert and deposit ProTherm data into ProtaBank studies

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

Multi-class signal peptide prediction and structure decoding model.

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

Listing of papers about machine learning for proteins.

A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design

A package to predict protein inter-residue geometries from sequence data

ThermoNet is a computational method for quantitative prediction of the impact of single-point mutations on protein thermodynamic stability. The core algorithm of ThermoNet is an ensemble of deep 3D…

Computational tools for extremely low-cost, massively parallel amplicon-based sequencing of every variant in protein mutant libraries.