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Perform fast functional enrichment on feature lists (like genes or proteins) using the hypergeometric distribution. Tailored for speed, this package is ideal for interactive platforms such as Shiny. It supports the retrieval of functional data from sources like GO, KEGG, Reactome, Bioplanet and WikiPathways. By downloading and preparing data first, it allows for rapid successive tests on various feature selections without the need for repetitive, time-consuming preparatory steps typical of other packages.

The package implements a method for normalising microarray intensities from single- and multiple-color arrays. It can also be used for data from other technologies, as long as they have similar format. The method uses a robust variant of the maximum-likelihood estimator for an additive-multiplicative error model and affine calibration. The model incorporates data calibration step (a.k.a. normalization), a model for the dependence of the variance on the mean intensity and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.

Open-source LLM-powered R&D agent framework automating data-driven AI solution building through automated research, development, and evolution; achieves top open-source performance on MLE-Bench with dual Researcher-Developer agents and supports research copilot, data mining, Kaggle, and quant R&D workflows (13.6K+ stars, MIT License, 2025-2026)

Semi-automated research assistant for academic research and software development, supporting Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding, experiments, writing, and publication (Galaxy-Dawn, 4.5K+ stars, MIT License, 2026)

Provides a consistent C++ class interface for reading from a variety of commonly used matrix types. Ordinary matrices and several sparse/dense Matrix classes are directly supported, along with a subset of the delayed operations implemented in the DelayedArray package. All other matrix-like objects are supported by calling back into R.

Unified Python framework for bulk, single-cell, and spatial RNA-seq multi-omics analysis with deep learning deconvolution (VAE) and graph neural networks, bridging Bindea, Bindea, scanpy and squidpy ecosystems (Nature Communications 2024)

The R package decemedip is a novel computational paradigm developed for inferring the relative abundances of cell types and tissues measure by methylated DNA immunoprecipitation sequencing (MeDIP-Seq). This paradigm allows using reference data from other technologies such as microarray or WGBS.

The scDiagnostics package provides diagnostic plots to assess the quality of cell type assignments from single cell gene expression profiles. The implemented functionality allows to assess the reliability of cell type annotations, investigate gene expression patterns, and explore relationships between different cell types in query and reference datasets allowing users to detect potential misalignments between reference and query datasets. The package also provides visualization capabilities for diagnostics purposes.

High-performance molecular simulation toolkit

Scalable genomic analysis.

Unified Python framework for extracellular electrophysiology, standardizing interfaces to 10+ ML-based spike sorting algorithms including Kilosort for reproducible neural spike sorting workflows (792+ stars, actively maintained)

StaphScope is an automated, locally-executable computational pipeline designed specifically for comprehensive Staphylococcus aureus genomic surveillance. It addresses the critical bottleneck in MRSA research by integrating seven essential genotyping methods into a single, cohesive workflow.

mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.

This tutorial aims to illustrate the process of ligand parameterization for a small molecule, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Ibuprofen small compound (3-letter code IBP, Drugbank code DB01050), a non-steroidal anti-inflammatory drug (NSAID) derived from propionic acid.

Saves the delayed operations of a DelayedArray to a HDF5 file. This enables efficient recovery of the DelayedArray's contents in other languages and analysis frameworks.

Java-based browser. Fast, efficient, scalable visualization tool for genomics data and annotations. Handles a large variety of formats.

Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformatics tools, SSH/WSL/GPU runtimes, and OpenAI/Anthropic models (857+ stars, 2026)

Utilities for working with CSV/Tab-delimited files.

Python package for segmenting geospatial data with the Segment Anything Model (SAM), enabling zero-shot object segmentation in satellite and aerial imagery for remote sensing and Earth observation (MIT, 4k+ stars)

AI co-author covering the entire research lifecycle — from an under-specified research direction to a published paper; includes ResearchStudio-Idea for evidence-grounded research ideation and ResearchStudio-Reel for turning finished papers into posters, narrated videos, blogs, and interactive reels; runs as skills on Claude Code and Codex (1.2K+ stars, MIT License, 2026)

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)

In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (<https://www.ensembl.org/info/data/biomart/index.html>). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. The most prominent examples of BioMart databases are maintained by Ensembl, which provides biomaRt users direct access to a diverse set of data and enables a wide range of powerful online queries from gene annotation to database mining.

This package performs a Gene Set Analysis with the approach adopted by PADOG on the genes that are reported as translationally regulated (ie. exhibit a significant change in TE) by the DeltaTE package. It can be used on its own to see the impact of translation regulation on gene sets, but it is also integrated as an additional analysis method within ReactomeGSA, where results are further contextualised in terms of pathways and directionality of the change.

Bring the power and flexibility of AnnData to the R ecosystem, allowing you to effortlessly manipulate and analyse your single-cell data. This package lets you work with backed h5ad and zarr files, directly access various slots (e.g. X, obs, var), or convert the data into SingleCellExperiment and Seurat objects.

Curated, accuracy-first collection of benchmarks for evaluating LLMs on scientific reasoning and discovery across mathematics, physics, chemistry, materials science, biology, and agentic science (subinium, 29+ stars, MIT License, 2026)

CebraEM is a bioinformatics tool for analyzing and processing large-scale imaging data, providing a pipeline for segmentation, annotation, and analysis with support for both Linux and Windows environments. It includes modules for core functionality, annotation, and network analysis, requiring specific dependencies and a conda environment for execution.

Simple and accurate de novo protein binder design pipeline using AlphaFold2 backpropagation, MPNN, and PyRosetta for automated binder discovery (bioRxiv 2024)

Rust implementations of algorithms and data structures useful for bioinformatics.

TaxSEA is an R package for Taxon Set Enrichment Analysis, which utilises a Kolmogorov-Smirnov test analyses to investigate differential abundance analysis output for whether there are alternations in a-priori defined sets of taxa from public databases (BugSigDB, MiMeDB, GutMGene, mBodyMap, BacDive and GMRepoV2) and collated from the literature. TaxSEA takes as input a list of taxonomic identifiers (e.g. species names, NCBI IDs etc.) and a rank (E.g. fold change, correlation coefficient). TaxSEA be applied to any microbiota taxonomic profiling technology (array-based, 16S rRNA gene sequencing, shotgun metagenomics & metatranscriptomics etc.) and enables researchers to rapidly contextualize their findings within the broader literature to accelerate interpretation of results.

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.

a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments.

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.

A small language for defining pipeline stages and linking them together to make pipelines.

The AnVIL is a cloud computing resource developed in part by the National Human Genome Research Institute. The main cloud-based genomics platform deported by the AnVIL project is Terra. The AnVILWorkflow package allows remote access to Terra implemented workflows, enabling end-user to utilize Terra/ AnVIL provided resources - such as data, workflows, and flexible/scalble computing resources - through the conventional R functions.

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

Provides a unified interface to a variety of GSEA techniques from different bioconductor packages. Results are harmonized into a single object and can be interrogated uniformly for quick exploration and interpretation of results. Interactive exploration of GSEA results is enabled through a shiny app provided by a sparrow.shiny sibling package.

Neuro-imaging file formats.

Quantum chemisttry web platform that brings all the necessary tools to perform quantum chemistry in a user-friendly web interface.

AlphaFold/ESMFold accessible implementation with AF3 JSON export, database updates

A Python package useful for chemistry (mainly physical/inorganic/analytical chemistry)

Provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files. GDS is portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited for large-scale datasets, especially for data which are much larger than the available random-access memory. The gdsfmt package offers the efficient operations specifically designed for integers of less than 8 bits, since a diploid genotype, like single-nucleotide polymorphism (SNP), usually occupies fewer bits than a byte. Data compression and decompression are available with relatively efficient random access. It is also allowed to read a GDS file in parallel with multiple R processes supported by the package parallel.

Java framework for processing biological data.

JCVI is a versatile toolkit for comparative genomics analysis. It is a collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

A transparent, unit-aware calculator for the mathematical relationship between peptide mass, target concentration and solution volume. It normalizes mg, micrograms, mL and microlitres, shows the formula and includes a reference syringe visualization. Research-use-only software: it does not select a solvent, validate a laboratory method, calculate a dose or provide administration guidance.

Web application and service for visualizing small- to medium-scale models of gene regulatory networks. It automatically lays out either an unweighted or weighted network graph based on an Excel input spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows. It is best-suited for visualizing networks of fewer than 35 nodes and 70 edges and has general applicability.