Find open-source science resources

Research coding benchmark curated by scientists with 338 subproblems across 16 subdomains (physics, math, materials, biology, chemistry), evaluating LLMs on realistic scientific programming tasks with gold-standard solutions (NeurIPS 2024)

PyTorch domain library for geospatial deep learning providing standardized datasets, samplers, transforms, and pre-trained models for remote sensing, land cover mapping, and environmental monitoring (Microsoft, 4K+ stars)

dadi is a bioinformatics tool for inferring demographic history and selection from genetic data using diffusion approximations, offering speed and flexibility in modeling population dynamics. It supports up to three populations with customizable parameters and provides efficient computational performance.

Python library for blazing-fast genomic interval operations and genomic file formats I/O on Polars DataFrames

PseudoScope is an automated, locally-executable computational pipeline designed specifically for comprehensive Pseudomonas aeruginosa genomic surveillance. It integrates seven essential analysis modules into a single, cohesive workflow: FASTA QC (assembly quality metrics), MLST (Oxford scheme), PAST serotyping (O-antigen typing), AMRFinderPlus (antimicrobial resistance gene detection), ABRicate (multi-database screening for resistance, virulence, plasmids, biocides), Ultimate Reporter (gene-centric integration with interactive HTML), and Visualisation Dashboard (publication-ready interactive plots including PCA, networks, boxplots). PseudoScope runs entirely locally (or on HPC clusters), protects data privacy, and produces beautiful interactive reports in minutes.

Kleboscope is an automated, locally‑executable computational pipeline designed specifically for comprehensive Klebsiella pneumoniae genomic surveillance. It addresses the growing threat of multidrug‑resistant and hypervirulent K. pneumoniae by integrating eight essential analysis modules into a single, cohesive workflow. Kleboscope offers two complementary report views: Gene‑centric – each gene is shown with all genomes that contain it, together with its frequency, enabling rapid cross‑genome pattern discovery; and Sample‑centric – each isolate gets its own interactive box with typing badges (MLST, K‑locus, O‑locus, hypervirulence), per‑database tables (AMR, Virulence, BACMET, Plasmids), and full mutation details – perfect for clinical reports and patient‑level investigations.

Python library to train, interpret, and apply deep learning models to DNA sequences, providing a unified framework for regulatory genomics with support for CNN and transformer architectures, variant effect prediction, and attribution analysis (325+ stars)

AcinetoScope is an automated, comprehensive bioinformatics pipeline designed specifically for the genomic analysis of Acinetobacter baumannii, a WHO Critical Priority pathogen responsible for devastating hospital-acquired infections. It integrates seven analysis types (MLST, ABRicate, AMRFinder, Kaptive 3, APT, PlasmidFinder, and mutation detection) into a single automated workflow — from FASTA to actionable insights. The pipeline offers both gene-centric and sample-centric reporting, dynamic grouping by typing, and is optimised for HPC, cloud, and container environments.

Ensemble of automated QM workflows that can be run through jupyter notebooks, command lines and yaml files.

Neuro-imaging file formats.

Family of codon-resolution language models trained on 130 million protein-coding sequences from over 20,000 species, enabling cross-species gene expression prediction and codon-level functional genomics (2025)

Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs (460+ stars, 2024)

Controllable foundation model for general and specialized biomolecular structure prediction across proteins, nucleic acids, and complexes, featuring a public web server for interactive prediction workflows (IntelliGen AI, 223+ stars, Apache 2.0, 2025)

Meta's comprehensive ML ecosystem for materials/chemistry with 118M+ DFT calculations, EquiformerV2 models achieving top Matbench Discovery performance

Convert AMBER forcefields from ANTECHAMBER to GROMACS format.

Multi-agent system automatically transforming research papers into interactive AI agents with MCP server generation, tutorial auto-detection, and benchmark extraction (2.2K+ stars, MIT License, 2025)

Microsoft's generative model for sampling protein equilibrium conformations 100,000× faster than MD simulations, predicting domain motions, local unfolding and cryptic binding pockets on a single GPU (Science 2025)

A library for processing, analyzing and modeling spectroscopic data.

The HGVS Nomenclature is an internationally-recognized standard for the description of DNA, RNA and protein sequence variants. It is used to convey variants in clinical reports and to share variants in publications and databases. The HGVS Nomenclature is administered by the [HGVS Variant Nomenclature Committee (HVNC)](https://hgvs-nomenclature.org/stable/hvnc/) under the auspices of the [Human Genome Organization (HUGO)](https://hugo-int.org/).

Curated library of 550+ medical research agent skills spanning evidence insights, protocol design, omics/clinical data analysis, and academic writing; each skill is reviewed through MedSkillAudit and compatible with Claude Code, Codex, Open Code, OpenClaw, and SKILL.md-compatible agents (AIPOCH, 1.2K+ stars, MIT License, 2026)

IBM's open foundation model family for materials and chemistry, covering SMILES, SELFIES, molecular graphs, 3D atom positions, and electron density grids, with a unified toolkit for representation learning and downstream prediction/generation (Apache 2.0, 2024-2025)

Some IDs may represent experiment sets, e.g. https://www.mavedb.org/#/experiment-sets/urn:mavedb:00000011 Others represent genomic regions (specifically deep mutational scans thereof) e.g. https://www.mavedb.org/#/experiment-sets/urn:mavedb:00000011-a

Agricultural machine learning platform

Deep learning-based multi-animal pose tracking and behavior classification, enabling automated quantification of social interactions and collective behavior across species (Nature Methods 2022, 2.2K+ stars)

Offline tool for cleaning tables of human gene and protein identifiers (TXT, CSV, TSV, XLSX). It maps approved symbols, aliases, previous symbols, Ensembl gene, UniProt, Entrez, RefSeq and HGNC identifiers to current HGNC approved symbols with cross-references, using a bundled HGNC snapshot. Excel date-corrupted symbols are recovered where the original is unambiguous and flagged for manual review otherwise; no input row is dropped. Each run records the tool version and HGNC release and writes a per-row audit table.

Google DeepMind's official collection of agentic science skills accelerating scientific workflows with better grounding and higher token efficiency, integrating insights from AlphaGenome, AFDB, UniProt and 30+ other databases and tools (2026)

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)

Python framework for writing high-performance GPU simulation and graphics kernels with first-class automatic differentiation, enabling differentiable physics, molecular dynamics, soft-body and cloth simulation, robotics, and CFD adjoints compiled to CUDA; serves as the underlying engine for differentiable simulation projects like Newton and integrates with PyTorch, JAX, and OpenUSD (NVIDIA, 7.1K+ stars, Apache 2.0)

PyTorch-based differentiable programming framework for physics-informed system identification, parametric constrained optimization, and model predictive control, integrating neural operators, neural ODEs, KANs, SINDy, and differentiable predictive control with 30+ tutorials (1.3k+ stars, BSD License)

An ontology with predicates to formalization of the concept of mentions. The mentions may be either explicit (e.g. as when well stated into an article "Dr. Johnson's groundbreaking research on climate change") or implicit (e.g. such as discussing "seminal studies in the field"). MiTO contains the object property mito:mentions and its inverse mito:isMentionedBy.

Microsoft's foundation model for the Earth system supporting weather, air pollution, and ocean wave forecasting at multiple resolutions, trained on 1M+ hours of diverse atmospheric data (Nature 2025)

Minimalist, batteries-included repository for training video world models with diffusion-forcing, supporting long-horizon rollouts, 3D point-cloud generation, and model-predictive control with pretrained checkpoints (Simchowitz Lab, 700+ stars, MIT License, 2026)

An EMMO-based domain ontology for atomistic and electronic modelling.

An ontology that provides a structured vocabulary for rhetorical elements within documents (e.g., Introduction, Discussion, Acknowledgements, Reference List, Figures, Appendix). It is imported by DoCO.

Generates pre-miRNA and mature miRNA count tables from read alignments to pre-miRNA sequences and a gff file, both downloaded from mirBase. Produces also read coverage plots of pre-miRNAs.

PyTorch-native atomistic simulation engine for the machine-learned interatomic potential (MLIP) era, enabling batched molecular dynamics and structural relaxation with automatic GPU memory management; supports MACE, Fairchem, SevenNet, ORB, MatterSim and other popular MLIPs with up to 100x speedup over ASE (Radical AI, AI for Science 2026, 468+ stars, MIT License)

Modular framework for AI-driven scientific and algorithmic discovery, providing a unified interface for implementing, running, and fairly comparing discovery algorithms across 200+ optimization tasks; introduces AdaEvolve and EvoX adaptive/evolutionary algorithms and natively supports OpenEvolve, GEPA, and Harbor-format benchmarks (skydiscover-ai, 568+ stars, Apache 2.0, 2026)

Open source PEM (Proton Exchange Membrane) fuel cell simulation tool.

Open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives, enabling quantum algorithm development for quantum chemistry, materials science, and optimization research (IBM, 7.4K+ stars, Apache 2.0)

An ontology that allows the description of numerical and categorical bibliometric data (e.g., journal impact factor, author h-index, categories describing research careers) in RDF.

High-accuracy PDF→Markdown/JSON/HTML conversion, specialized for tables/formulas/code blocks with benchmark scripts

HIDE-Deconv is a framework for characterizing cellular remodeling from bulk RNA-seq data using hierarchical cell-type deconvolution across multiple levels of cellular resolution. It provides an integrated workflow for single-cell reference preprocessing, estimation of cellular compositions, and downstream analysis of deconvolution results, including visualization, clustering, differential composition, and survival analysis.

Evolvable and privacy-preserving multi-agent framework automating, scaling, and accelerating data sciences with a particular focus on end-to-end single-cell biology analyses; features agentic code evolution, multi-agent team orchestration, distributed architecture, and a community marketplace with 1,000+ curated agents and skills (428+ stars)

Terms for genes, experimental factors, and cell lines used by the [Gemma platform](https://gemma.msl.ubc.ca/home.html) for differential gene expression analysis.

Flow-matching protein folding model using only general-purpose transformer layers, scaled to 3B parameters and trained on 8.6M+ distilled structures; challenges the reliance on complex domain-specific architectures and supports PyTorch and MLX backends with model sizes from 100M to 3B parameters (985+ stars, MIT License)

Large-scale knowledge graph and pip-installable client for literature-grounded automated scientific research, connecting papers, authors, institutions, venues, keywords, citations, and a four-level research taxonomy across medicine, social sciences, engineering, computer science, materials science, and more (ZJU NLP, arXiv 2026, 136+ stars, MIT License)

The Ontology of Immune Epitopes (ONTIE) is an effort to represent terms in the immunology domain in a formal ontology with the specific goal of representing experiments that identify and characterize immune epitopes.

Ontology representation of the [International Committee on Taxonomy of Viruses (ICTV)](https://ictv.global/) for the [EVORA project](https://evora-project.eu/)

Deterministic, rule-based variant interpretation platform for clinical genetics laboratories. Automates ACMG/AMP 2015 classification using a Bayesian point-based framework (Tavtigian et al. 2018) with BayesDel ClinGen SVI-calibrated thresholds (Pejaver et al. 2022). Integrates 8 reference databases (gnomAD v4.1, ClinVar, dbNSFP 4.9c, SpliceAI, gnomAD Constraint, HPO, ClinGen, Ensembl VEP). Analyzes nuclear and mtDNA variants, structural and copy-number variants (SV/CNV), with trio/family and cohort analysis. Supports HPO-based phenotype matching, biomedical literature mining across 2M+ PubMed publications, and structured clinical report generation. AI assists in evidence synthesis but does not make classification decisions. EU-hosted on dedicated infrastructure in Helsinki, Finland (GDPR-compliant).