Find open-source science resources

GenBio AI's software stack for the AI-Driven Digital Organism, supporting adaptation and finetuning of multiscale biological foundation models across DNA, RNA, protein, structure, and single-cell tasks with reproducible CLIs and pretrained model zoo (2025)

Foundation models for genomics and transcriptomics pretrained on 3,000+ human genomes and 850+ diverse species, enabling chromatin accessibility prediction, splice site detection, and promoter classification across multiple model scales (InstaDeep, NVIDIA & TUM, Nature Methods 2023)

Universal pretrained neural network potential with charge and magnetic moment awareness, trained on 1.5M+ Materials Project inorganic structures for charge-informed molecular dynamics and phase diagram prediction (Berkeley, Nature Machine Intelligence 2023 Cover)

Euclidean neural networks for arbitrary point transformations enabling E(3)-equivariant deep learning, foundational library for building geometry-aware neural networks in molecular dynamics, materials science, and physics

Self-supervised vision foundation model for generalized structural brain MRI analysis, pretrained on ~49,000 scans from diverse datasets and generalizing across brain age prediction, dementia/MCI classification, IDH mutation detection, glioma survival prediction, time-to-stroke estimation, MR sequence classification, and brain tumor segmentation; outperforms task-specific models especially with limited training data (Mass General Brigham & Harvard Medical School, 129+ stars)

Lightweight supervised slide foundation model with 0.9M parameters pretrained on 24K whole-slide images for pan-cancer morphological classification, achieving competitive performance with much larger self-supervised models (TITAN, GigaPath) while enabling finetuning on consumer-grade GPUs; includes standardized MIL implementations and benchmarking across 15+ classification tasks (Mahmood Lab, Harvard Medical School, 153+ stars)

A [Jupyter](https://jupyter.org/) widget to interactively view molecular structures and trajectories.

SCENIC+ is a python package to build gene regulatory networks (GRNs) using combined or separate single-cell gene expression (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq) data.

Official implementation of the second-generation fully autonomous scientific discovery system, extending the original with agentic tree search and reduced template dependency to achieve workshop-level accepted papers (6.7K+ stars, 2025)

First fully autonomous open-ended scientific discovery system with official implementation: hypothesis→experiment→writing→review simulation (13.8K+ stars, 2024)

Biocaml aims to be a high-performance user-friendly library for Bioinformatics.

Graph neural network operating entirely at the atomic level for protein-ligand conformational ensemble prediction and docking, generating diverse solutions through rapid stochastic denoising to model conformational heterogeneity (Baker Lab, bioRxiv 2025)

Conversational data analysis using natural language

AI-assisted mutation nomination approach optimizing protein function by integrating structural and evolutionary constraints into protein inverse folding models, compatible with ProteinMPNN, LigandMPNN, ESM-IF1, and SaProt (Chinese Academy of Sciences, 359+ stars)

Another list focuses on Python stuff related to Chemistry.

Cheminformatic extension for the SQLAlchemy database.

SIMD C library for global, semi-global, and local pairwise sequence alignments

NIST's open-source platform for data-driven atomistic materials design, integrating DFT datasets (JARVIS-DFT), machine learning property prediction (JARVIS-ML), and a comprehensive leaderboard for benchmarking materials AI methods across the periodic table (384+ stars)

Large-scale flow-based protein backbone generator utilizing hierarchical fold class labels for conditioning with a tailored scalable transformer architecture, enabling controllable de novo protein design (264+ stars)

DeepSeek's open-source large language model for formal theorem proving in Lean 4, integrating informal and formal mathematical reasoning through recursive subgoal decomposition and reinforcement learning powered by DeepSeek-V3, with open weights and ProverBench evaluation (2025)

In silico directed evolution framework using few-shot active learning to optimize protein activities, enabling rapid protein engineering with minimal experimental data (352+ stars, 2023)

animalcules is an R package for utilizing up-to-date data analytics, visualization methods, and machine learning models to provide users an easy-to-use interactive microbiome analysis framework. It can be used as a standalone software package or users can explore their data with the accompanying interactive R Shiny application. Traditional microbiome analysis such as alpha/beta diversity and differential abundance analysis are enhanced, while new methods like biomarker identification are introduced by animalcules. Powerful interactive and dynamic figures generated by animalcules enable users to understand their data better and discover new insights.

GRIDSS: the Genomic Rearrangement IDentification Software Suite.

Systematic medical RAG toolkit for question answering over PubMed, StatPearls, textbooks, and Wikipedia, supporting multiple retrievers, domain LLMs, and follow-up-query workflows for benchmarked clinical/biomedical QA (ACL Findings 2024)

General-purpose pathology foundation model pretrained on 100K+ diagnostic whole-slide images across 20 major tissue types, achieving state-of-the-art transfer learning across 30+ clinical tasks and serving as a universal feature extractor for digital pathology (Mahmood Lab, 722+ stars)

Vision-language pathology foundation model using contrastive learning on histopathology image-text pairs, enabling zero-shot classification, slide-level retrieval, and multimodal reasoning across diverse cancer types (Mahmood Lab, 494+ stars)

Python wrapper for [bedtools](https://github.com/arq5x/bedtools).

A database system designed to store, organize, and manage large-scale nucleotide sequencing read data (like PacBio reads) for the Dazzler genome assembler

Descriptor computation(chemistry) and (optional) storage for machine learning.

SKESA is a de-novo sequence read assembler for microbial genomes. It uses conservative heuristics and is designed to create breaks at repeat regions in the genome. This leads to excellent sequence quality without significantly compromising contiguity.

This packages simulates spatial transcriptomics data with the mean- variance relationship using a Gaussian Process model per gene.

Universal chart comprehension and reasoning model

Circlator is a tool to circularize genome assemblies. It will attempt to identify each circular sequence and output a linearised version of it. It does this by assembling all reads that map to contig ends and comparing the resulting contigs with the input assembly.

k-mer counting, filtering, and graph traversal.

NOVOPlasty - The organelle assembler and heteroplasmy caller. NOVOPlasty is a de novo assembler and heteroplasmy/variance caller for short circular genomes..

A VCF Parser for Python.

Displaying sequence statistics for next-generation sequencing.

Educational resource on performing RNA-seq analysis in the cloud using Amazon AWS cloud services. Topics include preparing the data, preprocessing, differential expression, isoform discovery, data visualization, and interpretation.

Open source web framework for small molecule analysis based on Django.

Learning nonlinear operators

AI for chemical reaction prediction and synthesis planning

FASTQ/A short-reads pre-processing tools: Demultiplexing, trimming, clipping, quality filtering, and masking utilities.

Finds SNP sites from a multi-FASTA alignment file.

Customizable pipeline for differential expression analysis with an intuitive GUI.

Flexible circular visualization of genome-associated data with BioPerl and SVG.

Horizon chart D3-based JavaScript library for DNA data.