Repository Index

Official git repository for Biopython (originally converted from CVS)

• python
• bioinformatics
• genomics
• biopython

Official repository for the Boltz biomolecular interaction models

• binding-prediction
• drug-discovery
• protein-structure

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

• pytorch
• protein-structure
• alphafold2

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

• deep-learning
• protein-sequences
• protein-structure
• semi-supervised-learning

Official release of the ProGen models

• language-model
• protein
• generative-model

Generation of protein sequences and evolutionary alignments via discrete diffusion models

• discrete-diffusion
• generative-model
• multiple-sequence-alignment
• protein-sequences

OmegaFold Release Code

A Python Package for Protein Dynamics Analysis

• python
• protein
• dynamics

Generative biopolymer design with rich conditioning.

A dependency-free cross-platform swiss army knife for PDB files.

• python
• protein
• pdb
• bioinformatics

Source code for "DeepDTA: deep drug-target binding affinity prediction"

• protein-ligand-interactions
• convolutional-neural-networks

Ankh: Optimized Protein Language Model

LLM for Drug Editing, ICLR 2024

• chatgpt
• conversation
• drug
• drug-discovery

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524

• self-attention
• compound-protein-interaction
• transformercpi
• structure-free-virtual-sreening

Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.

• alphafold3
• docking
• drug-design
• drug-discovery

PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"

Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).

• deep-reinforcement-learning
• generative-model
• vae
• molecule-generation

Python library for statistical analysis of mRNA and protein distributions in fluorescent microscopy images