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AI coding agent skills for KiCad electronics design that turn Claude Code, Codex, Gemini CLI, and other coding agents into full electronics design assistants; parses schematics and PCB layouts, builds power trees, audits connectors/ESD protection, validates passive networks, runs SPICE simulation, sources components from major distributors, and prepares boards for fabrication (aklofas, 974+ stars, MIT License, 2026)

Local-first autonomous research system implementing a Git-like research protocol for long-running scientific discovery; explores competing explanations, executes experiments inside an isolation boundary, self-criticizes results, and exports the entire path as typed Agent-Native Research Artifacts (ARA) with exploration DAGs, claim-to-evidence anchors, content hashes, and re-execution hooks (126+ stars, Apache 2.0, arXiv 2026)

First unified Lean 4 framework for neural-network specification, execution, and verification; tensor shapes are part of the types, models are executable Lean programs, and the same definitions can be used by training code, graph transformations, certificate checkers, and proofs with CPU/CUDA backends (123+ stars, MIT License)

A taxonomy-informed sparse DNA foundation model for microbial genomics.

The Bioregistry is integrative meta-registry of biological databases, ontologies, and nomenclatures that is backed by an open database.

A Python package for protein dynamics analysis

A data model for managing information about chemical entities, ranging from atoms through molecules to complex mixtures.

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein…

Hand-curated Snakemake pipelines to combine identifier cross-references from multiple sources across dozens of biomedical types, including anatomical entities, diseases and phenotypes, genes and proteins and many others.

Python package for Dynamic Mode Decomposition (DMD) and its variants (exact, incremental, multiresolution MR-DMD, higher-order HODMD, parametric, BOP-DMD, DMD-control, and DL-DMD neural-network extensions), enabling data-driven reduced-order modeling, Koopman operator analysis, and flow-field feature extraction for high-dimensional dynamical systems in fluid dynamics and scientific computing (1.2K+ stars, MIT License, actively maintained)

Madrimed1.2 2B GGUF Optimized GGUF Quantization Tiers for MadriMed 1.2 (2B Medical Mulitmodel)

Nemo (MAMBO_v3) identifies adult moths and butterflies in photographs, predicting 12,632 species, 4,476 genera and 104 families. Predictions use GBIF taxon IDs.

Co-create PowerPoint presentations with Generative AI from documents or topics

Statial is a suite of functions for identifying changes in cell state. The functionality provided by Statial provides robust quantification of cell type localisation which are invariant to changes in tissue structure. In addition to this Statial uncovers changes in marker expression associated with varying levels of localisation. These features can be used to explore how the structure and function of different cell types may be altered by the agents they are surrounded with.

First physics-aligned interactive benchmark for LLM agents in engineering construction, designing rockets/cars/bridges in physics simulator with 3D spatial geometry library

An issue on the Gene Ontology GitHub issue tracker

Open-source image analysis toolkit for high-throughput plant phenotyping, extracting morphological, color, and texture traits from RGB, hyperspectral, and thermal imagery with modular Python workflows for crop improvement, stress detection, and plant biology research (Donald Danforth Plant Science Center, 795+ stars, MPL-2.0)

Low- and high-level wrappers for Gemma's RESTful API. They enable access to curated expression and differential expression data from over 10,000 published studies. Gemma is a web site, database and a set of tools for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles.

Molecular dynamics analysis

Multi-type data labeling and annotation tool

Ensemble of automated machine learning protocols that can be run sequentially through a single command line. The program works for regression and classification problems.

An ontology in the OBO foundry, not exactly the same as the obo namespace

The Common Core Ontologies (CCO) comprise twelve ontologies that are designed to represent and integrate taxonomies of generic classes and relations across all domains of interest. CCO is a mid-level extension of Basic Formal Ontology (BFO), an upper-level ontology framework widely used to structure and integrate ontologies in the biomedical domain (Arp, et al., 2015). BFO aims to represent the most generic categories of entity and the most generic types of relations that hold between them, by defining a small number of classes and relations. CCO then extends from BFO in the sense that every class in CCO is asserted to be a subclass of some class in BFO, and that CCO adopts the generic relations defined in BFO (e.g., has_part) (Smith and Grenon, 2004). Accordingly, CCO classes and relations are heavily constrained by the BFO framework, from which it inherits much of its basic semantic relationships.

First bioinformatics-native AI agent skill library enabling local-first, reproducible genomic and population-genetics research workflows built on OpenClaw (871+ stars, MIT License, 2026)

Behavioral and neuroimaging experiments.

The Basic Register of Thesauri, Ontologies & Classifications (BARTOC) is a database of Knowledge Organization Systems and KOS related registries. The main goal of BARTOC is to list as many Knowledge Organization Systems as possible at one place in order to achieve greater visibility, highlight their features, make them searchable and comparable, and foster knowledge sharing. BARTOC includes any kind of KOS from any subject area, in any language, any publication format, and any form of accessibility. BARTOC’s search interface is available in 20 European languages and provides two search options: Basic Search by keywords, and Advanced Search by taxonomy terms. A circle of editors has gathered around BARTOC from all across Europe and BARTOC has been approved by the International Society for Knowledge Organization (ISKO).

PyTorch framework for training neural network interatomic potentials with the Equivariant Transformer (ET) architecture and its efficient TensorNet successor, providing equivariant message passing with linear complexity in tensor order; underpins the MACE-OFF and SPICE models and widely adopted across molecular dynamics and materials simulation workflows (Amsterdam Machine Learning Lab / De Fabritiis Group, 483+ stars, MIT License, actively maintained)

BioTools is a registry of databases and software with tools, services, and workflows for biological and biomedical research.

edfcore is a zero-dependency TypeScript library for reading EDF, EDF+, BDF, and BDF+ physiological recordings in browser and Node.js applications. It provides programmatic access to biosignal samples, channel metadata, per-channel sampling rates, physical units, annotations, and discontinuous recording timelines.

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

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

Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existing ExpressionSet object. The pure dependency on R/Bioconductor guarantees maximum flexibility in the statistical analysis in the back-end. Once the ExpressionSet is prepared, it can be visualized using the front-end, implemented by shiny and plotly. Both features and samples could be selected from (data) tables or graphs (scatter plot/heatmap). Different types of analyses, such as enrichment analysis (using Bioconductor package fgsea or fisher's exact test) and STRING network analysis, will be performed on the fly and the results are visualized simultaneously. When a subset of samples and a phenotype variable is selected, a significance test on means (t-test or ranked based test; when phenotype variable is quantitative) or test of independence (chi-square or fisher’s exact test; when phenotype data is categorical) will be performed to test the association between the phenotype of interest with the selected samples. Additionally, other analyses can be easily added as extra shiny modules. Therefore, omicsViewer will greatly facilitate data exploration, many different hypotheses can be explored in a short time without the need for knowledge of R. In addition, the resulting data could be easily shared using a shiny server. Otherwise, a standalone version of omicsViewer together with designated omics data could be easily created by integrating it with portable R, which can be shared with collaborators or submitted as supplementary data together with a manuscript.

The Context and Measurement Ontology (COMO) contains ontological terms to describe the context for various types of experimental data and measurements. It is useful in its current state for several different environmental microbiology projects. This ontology is used in multiple CORAL (Contextual Ontology-based Repository Analysis Library) deployments.

Translate differential transcript usage results into discrete splice events.

Universal molecular toolkit that can be used for molecular fingerprinting, substructure search, and molecular visualization written in C++ package, with Java, C#, and Python wrappers.

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

Continuously updated functional re-annotation of the Mycobacterium tuberculosis complex gene set, anchored on the MTBC0 ancestral genome rather than on a single strain. Serves one record per gene combining Pfam domains, ESMFold structures with Foldseek search, protein language-model features, orthology, curated knowledge, protein association networks and intra-species selection inferred from 145209 sequenced genomes, with dated sources and a graded confidence level for every field. Intended as a successor to Mycobrowser, which is no longer maintained.

A collection of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and transport processes.

A benchmark for ML-guided high-throughput materials discovery.

Modern LLM-native agent simulation platform for social science research and experimental design, providing a flexible framework for creating and managing intelligent agents in simulated environments (Tsinghua FIB Lab, 984+ stars, 2025)

A 2B-parameter multimodal medical vision-language model, trained for medical image understanding, radiology report assistance, clinical visual question answering, and medical text reasoning.

The DCAT-AP conversion to a LinkML Schema is the intended point of truth for the DCAT-AP+ schema, but could be used alternatively as a LinkML representation of DCAT-AP for other Projects. It is a port of DCAT-AP to the LinkML world that is as faithful to the original as possible. This Persistent Identifier does not only provide the SHACL Shape, but could also be used as described [here](https://github.com/perma-id/w3id.org/tree/cecbc2e5f40d928f05ed5306d24fc60db0e7bb21/nfdi-de/dcat-ap-plus). DCAT-AP+ is a [LinkML](https://linkml.io/)-based extension of the [DCAT Application Profile 3.0](https://semiceu.github.io/DCAT-AP/releases/3.0.0/) that adds a provenance layer for describing how a dataset was generated and what it is about, using the [Starting Point Terms of PROV-O](https://www.w3.org/TR/prov-o/#description-starting-point-terms), the [QUDT ontology](https://www.qudt.org/), and [Dublin Core Terms](http://purl.org/dc/terms/).

This is an R/shiny package to perform functional enrichment analysis for microbiome data. This package was based on clusterProfiler. Moreover, MicrobiomeProfiler support KEGG enrichment analysis, COG enrichment analysis, Microbe-Disease association enrichment analysis, Metabo-Pathway analysis.

Semi-autonomous AI scientist for scientific theory discovery and verifiable goal solving, using adversarial review-refinement loops and evolution-inspired candidate populations; integrates with Claude Code, Gemini CLI, Antigravity, and Codex harnesses (Imbue, 31+ stars, AGPL-3.0, 2026)

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

A modeling paradigm-specific registry of prefixes and their URL expansions

The System Package Data Exchange™ (SPDX®) specification is an open standard designed to represent systems containing software components as Software Bill of Materials (SBOMs). Additionally, SPDX supports AI, data, and security references, making it suitable for a wide range of risk management use cases. This _spdx3_ prefix is for SPDX 3.x versions. For earlier versions, use _spdx.term_.

BRANCHSNV reports strict clade-exclusive nucleotide markers separately from single-nucleotide substitutions reconstructed on a selected edge of a rooted phylogenetic tree, while retaining ambiguity across equally parsimonious ancestral-state reconstructions.