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

Chai-1, SOTA model for biomolecular structure prediction

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

• kmer
• dnabert-model
• kmer-format
• gpu

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

Sequential regulatory activity predictions with deep convolutional neural networks.

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

• python
• protein
• pdb
• bioinformatics

GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations

Schema and generated objects for biolink data model and upper ontology

• biolink
• monarchinitiative
• gene-ontology
• datamodel

RNA-seq prediction with deep convolutional neural networks.

Bi-Directional Equivariant Long-Range DNA Sequence Modeling

A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.

OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.

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

Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

Accurate and efficient spot detection for microscopy data

Learning cell communication from spatial graphs of cells

• tensorflow
• gnn
• glm
• cvae

code to run sei and obtain sei and sequence class predictions

Toolbox for the analysis of smFISH images.

• pattern-classification
• rna-localization
• segmentation
• smfish

NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions

• computational-biology
• bioinformatics
• graph-convolution
• deep-learning

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

scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection