Find open-source science resources

World's first fully open, accelerated weather AI software stack with Medium Range forecasting and Nowcasting models using generative AI (January 2026)

Provides R wrappers of several on-target and off-target scoring methods for CRISPR guide RNAs (gRNAs). The following nucleases are supported: SpCas9, AsCas12a, enAsCas12a, and RfxCas13d (CasRx). The available on-target cutting efficiency scoring methods are RuleSet1, RuleSet3, DeepHF, enPAM+GB, and CRISPRscan. Both the CFD and MIT scoring methods are available for off-target specificity prediction. The package also provides a Lindel-derived score to predict the probability of a gRNA to produce indels inducing a frameshift for the Cas9 nuclease. Note that DeepHF and enPAM+GB are not available on Windows machines.

The package provides `rlang` data masks for the SummarizedExperiment class. The enables the evaluation of unquoted expression in different contexts of the SummarizedExperiment object with optional access to other contexts. The goal for `plyxp` is for evaluation to feel like a data.frame object without ever needing to unwind to a rectangular data.frame.

A mixture-of-experts foundation model for tabular classification.

Fast, interactive, multi-dimensional image viewer for Python, foundational platform for scientific imaging AI with a rich plugin ecosystem integrating deep learning segmentation, object tracking, and microscopy analysis workflows (2.6K+ stars)

BOLD-Local-DB converts the public TSV/tar.gz data package downloaded from BOLD Systems into a local, indexed SQLite database that can be searched entirely offline. It has two components: a Creator (desktop GUI) that filters, imports, indexes, and optionally adds full-text search to the downloaded data; and a local web viewer for advanced field search, full-text search, batch search by term list, and CSV/FASTA export. Intended for researchers who need to query large BOLD exports (DNA barcode records, taxonomy, collection metadata) repeatedly without depending on an internet connection or BOLD's rate limits.

LoRA adapters fine-tuning Qwen2.5-7B-Instruct to emit a full CIF crystal structure from a prompt of reduced composition + target space-group number. Part of a controlled composition-sweep study (MP-20 : MPTS-52 training ratio at fixed volume/steps).

R package for analysis of transcript and translation features through manipulation of sequence data and NGS data like Ribo-Seq, RNA-Seq, TCP-Seq and CAGE. It is generalized in the sense that any transcript region can be analysed, as the name hints to it was made with investigation of ribosomal patterns over Open Reading Frames (ORFs) as it's primary use case. ORFik is extremely fast through use of C++, data.table and GenomicRanges. Package allows to reassign starts of the transcripts with the use of CAGE-Seq data, automatic shifting of RiboSeq reads, finding of Open Reading Frames for whole genomes and much more.

Motivation-driven academic writing system for Claude Code, Codex, OpenClaw, and Hermes CLI that learns from strong papers, builds evidence-aware central-argument blueprints, and rewrites manuscripts with revision matrices and LaTeX-safe audits (4.9K+ stars, MIT License, 2026)

systemPipeShiny (SPS) extends the widely used systemPipeR (SPR) workflow environment with a versatile graphical user interface provided by a Shiny App. This allows non-R users, such as experimentalists, to run many systemPipeR’s workflow designs, control, and visualization functionalities interactively without requiring knowledge of R. Most importantly, SPS has been designed as a general purpose framework for interacting with other R packages in an intuitive manner. Like most Shiny Apps, SPS can be used on both local computers as well as centralized server-based deployments that can be accessed remotely as a public web service for using SPR’s functionalities with community and/or private data. The framework can integrate many core packages from the R/Bioconductor ecosystem. Examples of SPS’ current functionalities include: (a) interactive creation of experimental designs and metadata using an easy to use tabular editor or file uploader; (b) visualization of workflow topologies combined with auto-generation of R Markdown preview for interactively designed workflows; (d) access to a wide range of data processing routines; (e) and an extendable set of visualization functionalities. Complex visual results can be managed on a 'Canvas Workbench’ allowing users to organize and to compare plots in an efficient manner combined with a session snapshot feature to continue work at a later time. The present suite of pre-configured visualization examples. The modular design of SPR makes it easy to design custom functions without any knowledge of Shiny, as well as extending the environment in the future with contributions from the community.

A quantum chemistry package written in Python.

Turn any AI agent into a life science expert with NVIDIA BioNeMo skills, enabling agentic workflows for drug discovery, protein engineering, and biomolecular design (329+ stars, Apache 2.0 / CC-BY-4.0, 2026)

Open-source implementation of AlphaEvolve's evolutionary coding agent paradigm, enabling LLMs to autonomously discover and optimize algorithms through iterative evolution, matching the approach behind DeepMind's breakthrough matrix multiplication discovery (6.2K+ stars, 2025)

For a convenient overview and download list, visit our model page for this model.

A Core ML conversion of Na0s/Medical-Whisper-Large-v3, a medical fine-tune of openai/whisper-large-v3, for WhisperKit on Apple Silicon, with the encoder and the decoder running on the Apple Neural Engine.

Plain-text, git-tracked electronic lab notebook (ELN) for reproducible bioinformatics — threads your R & Python figures into living lab notes with full provenance. Built for single-cell / CyTOF / flow cytometry; works with Obsidian, Quarto & Jupyter.

Every model published in lab-cosmo/upet (the PET-MAD / UPET family), converted for pet-kokkos, a C++/Kokkos implementation of PET that runs without libtorch on CPUs and on NVIDIA and AMD GPUs.

PureJsImage is a free, open-source TypeScript library for decoding, inspecting, processing, and converting ordinary images and scientific rasters in Node.js and modern browsers. It provides explicit readers for microscopy, whole-slide pathology, medical imaging, electron microscopy, spectroscopy, hyperspectral, and multidimensional array formats. These include OME-TIFF, OME-Zarr, Aperio SVS, DICOM, NIfTI, MRC/CCP4, NRRD, DigitalMicrograph, EMD, ENVI, and FITS. Range-backed readers can request selected regions, tiles, volume planes, and metadata while preserving native numeric samples where supported. The default package has no runtime dependencies. Optional JPEG and PNG WebAssembly accelerators require explicit registration.

Open-source AI workbench for scientific research that automates the full research loop — literature review, hypothesis generation, code writing, experiment execution, database querying, and report writing — with 290+ skills, specialized research agents, and a browser-based workspace (1453+ stars, Apache 2.0, 2026)

High-performance, GPU-accelerated library for key computational chemistry tasks including molecular similarity, conformer generation, and geometry relaxation, designed to accelerate drug-discovery and molecular-modeling workflows (264+ stars, Apache 2.0)

Universal components for differentiable scientific computing, packaging heterogeneous scientific tools into self-contained, portable, gradient-propagating components with auto-generated schemas, CLI/REST API/Python SDK interfaces, and reproducible deployment across local, cloud, and HPC environments (105+ stars, Apache 2.0)

Toolkit for large-scale whole-slide image processing supporting 22+ patch encoders (UNI, CONCH, Virchow, H-Optimus-0, etc.), slide encoders (TITAN, GigaPath, PRISM, CHIEF, Madeleine, Feather), tissue segmentation, and multi-GPU inference with end-to-end pipeline and smart resume for standardized deployment of computational pathology foundation models (Mahmood Lab, Harvard Medical School, 553+ stars)

This repository contains the official model of the paper A Unified Predictive and Generative Solution for Liquid Electrolyte Formulation.

Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science with 140+ ready-to-use skills and 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Antigravity, and the open Agent Skills standard (K-Dense-AI, 26K+ stars, 2025)

Used to determine which cell types are enriched within gene lists. The package provides tools for testing enrichments within simple gene lists (such as human disease associated genes) and those resulting from differential expression studies. The package does not depend upon any particular Single Cell Transcriptome dataset and user defined datasets can be loaded in and used in the analyses.

High-performance, GPU-native molecular dynamics package supporting empirical potentials and neuroevolution potentials (NEPs) with a built-in `nep` training executable, achieving DFT-level accuracy at orders-of-magnitude lower training cost than competing MLIPs; widely adopted for heat transport (NEP/HNEP), lattice dynamics, mechanical properties, shock compression, and path-integral MD, with CUDA and ROCm support and extensive tutorials (849+ stars, GPL-3.0, Comput. Phys. Commun. 2017 / Phys. Rev. B 2021, actively maintained)

Biological vision foundation model trained on TreeOfLife-200M, yielding extraordinary accuracy on diverse biological visual tasks including habitat classification and trait prediction despite a narrow training objective (Ohio State University Imageomics Institute)

OpenTimsTDF is a standalone, cross-platform reader for Bruker timsTOF .tdf and .tdf_bin acquisition files, implemented in pure Rust with no dependency on vendor SDKs. Python bindings built on PyO3 expose frame, scan, and peak data as native Python objects, providing ion-mobility-aware access that can be assembled into a Pandas or Polars DataFrame.

This repository contains the model weights for Zatom-2, a unified atomistic model for generative modeling and representation learning across small molecules, periodic materials, and proteins. Introduced in Zatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains,…

MEG and EEG.

Neural differential equations in Julia

Modular Python suite for Neuro-AI research across all modalities, providing efficient data loaders (NeuralSet), curated datasets (NeuralFetch), scalable training (NeuralTrain), and unified benchmarking (NeuralBench) for building and evaluating neuroscience foundation models (Meta FAIR, 270+ stars, MIT License, 2026)

OpenProteo is the open-source Rust stack for proteomics raw-file access. It reads Thermo, Bruker, and Waters acquisitions through a single API (via the sibling OpenTFRaw, OpenTimsTDF, and OpenWRaw readers), converts them to PSI-MS mzML 1.1.0 with a canonical writer, and provides a zero-copy read_arrow() API (enabled by default) that loads directly into Polars or Pandas via PyArrow. No vendor SDKs, no Windows-only DLLs, no binary blobs in the release pipeline. Includes a one-shot vendor2mzml CLI.

seqlib is a type-safe Rust library for working with DNA and RNA sequences.

OpenWRaw is a standalone, cross-platform reader for Waters MassLynx .raw acquisition directories, implemented in pure Rust with no dependency on vendor DLLs. Python bindings built on PyO3 expose functions, scans, and ion-mobility data as native Python objects from Waters QTof and SYNAPT instrument families, ready to be assembled into a Pandas or Polars DataFrame.

OpenTFRaw is a standalone, cross-platform reader for Thermo Fisher Scientific .raw mass-spectrometry files, implemented in pure Rust with no dependency on vendor DLLs or .NET. Python bindings built on PyO3 return NumPy arrays for spectral data, straightforward to load into Pandas or Polars. Covers format versions 8 through 66 (LCQ Classic through Orbitrap Astral and modern TSQ instruments), supporting both centroid and profile spectra.

GPU-accelerated differentiable physics simulation engine built on NVIDIA Warp, supporting rigid/soft body, cloth, and gradient-based optimization for scientific ML, initiated by Disney Research, DeepMind, and NVIDIA (Linux Foundation, Apache 2.0, 2025)

Parameter/topology editor and molecular simulator with visualization capability.

A DNA annotation model from the Carbon family.

R Package for interactive visualization and browsing NGS data. It contains a browser for both transcript and genomic coordinate view. In addition a QC and general metaplots are included, among others differential translation plots and gene expression plots. The package is still under development.

Paper: RAGenome: Scaling Retrieval-Based Genomic Language Models to Long Contexts

Machine learning interatomic potentials

AlphaFold 3 inference pipeline for unified biomolecular structure prediction of proteins, nucleic acids, small molecules, ions, and post-translational modifications (Google DeepMind, Nature 2024)

NVIDIA's open-source platform for building and adapting biological AI models at scale, bundling ESM-2, Geneformer, MolMIM and DNA embedding models with recipes for single-GPU to multi-node training (2025)

This package contains utility functions used throughout the gDR platform to fit data, manipulate data, and convert and validate data structures. This package also has the necessary default constants for gDR platform. Many of the functions are utilized by the gDRcore package.

Open-source framework for building physics-ML models at scale (renamed from Modulus, 2025)

Open-source, all-atom biomolecular foundation model that turns co-folding into a scalable engine for structure prediction, design, and optimization across proteins, nucleic acids, and small molecules in drug discovery; ranked first on PXMeter-AB, FoldBench-AB, and 2026ARK-AB antibody-antigen benchmarks (263+ stars, Apache 2.0)

PyTorch library for training neural networks on gravitational-wave physics, providing differentiable PSD estimation, whitening, SNR calculation, interferometer response projection, waveform simulation, and streaming data loaders; the shared back end of the NSF A3D3/ML4GW pipelines deployed for real-time detection of compact-binary coalescences in LIGO–Virgo–KAGRA observing runs (35+ stars, GPL-3.0, 2022-2026)