Repository Index

Open source code for AlphaFold 2.

Official repository for the Boltz biomolecular interaction models

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

Code for running RFdiffusion

This package contains deep learning models and related scripts for RoseTTAFold

Chai-1, SOTA model for biomolecular structure prediction

Code for the ProteinMPNN paper

Deep probabilistic analysis of single-cell and spatial omics data

• scrna-seq
• variational-bayes
• variational-autoencoder
• cite-seq

The repository host gives no description.

• foundation-model
• gpt
• single-cell

Biological foundation modeling from molecular to genome scale

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.

Foundation Models for Genomics & Transcriptomics

• genomics
• deep-learning
• transformer
• dna

Official implementation for HyenaDNA, a long-range genomic foundation model built with Hyena

• foundation-models
• genomics
• language-models

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

A Go package for engineering organisms.

• synthetic-biology
• synbio
• genetic-engineering
• molecular-biology

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

[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome

• dataset
• dna
• dna-processing
• dna-training

RNA Velocity generalized through dynamical modeling

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

Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star

• dna
• language-model
• variant-effect-prediction
• genomics

UCE is a zero-shot foundation model for single-cell gene expression data

Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk

• bioinformatics
• exact-optimization
• metabolomics
• paired-data