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Modular toolchain for an extensible and customizable ETL pipeline that extracts, transforms, and loads clinical data and medical imaging metadata, applying dataset-specific mappings to generate outputs compatible with the EUCAIM Common Data Model (CDM). Its design aims to minimize manual data preparation efforts and facilitate customization and integration with other components, such as data quality assurance tools. Containerized, currently supports input datasets in CSV, JSON, XLSX.

spoQC is a modular framework for multimodal quality control (QC) of imaging-based spatially resolved transcriptomics (SRT). It independently evaluates cell segmentation, imaging, and transcript data to identify high-quality regions (HQRs) across entire tissue sections. In addition, spoQC uses Markov random fields (MRFs) to incorporate spatial dependencies and generate spatially refined QC masks.

PathForge is a modular benchmarking framework for multiple instance learning in computational pathology. It supports whole slide image feature extraction, HDF5 artifact generation, tile overviews, benchmarking, pipeline optimization, classification, regression, survival and retrieval tasks, and support for model inference and visualization.

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.

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 Intended as a successor to Mycobrowser, which is no longer maintained.

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.

nnU-Net is a self-configuring method for deep learning-based biomedical image segmentation, developed by the Applied Computer Vision Lab (ACVL) of Helmholtz Imaging and the Division of Medical Image Computing at the German Cancer Research Center (DKFZ). It is designed to automatically adapt to a given dataset, analyzing the provided training cases to configure a matching U-Net-based segmentation pipeline without requiring expertise from the user. The tool provides pretrained models for Pancreas and Pancreas tumor segmentation, Colon cancer primaries segmentation, Abdominal organ segmentation, Liver and liver tumor segmentation, Kidney and kidney tumor segmentation, Brain Tumor segmentation and Hippocampus (MR data) segmentation

PanAbyss is a tool for exploring and visualizing pangenome graphs. It allows users to search for and display regions of a pangenome using coordinates on a reference individual or based on annotations. It also enables searching for regions associated with a selected set of individuals (for example, those linked to a phenotype), computing proximity trees, and retrieving sequences from a given region.

A Molecular Interaction-Guided Graph Learning Framework for Multi-Omics Cancer Classification

Create MSP files containing the isotopic patterns for given molecules with given adducts. The tool is based on enviPat and the RforMassSpectrometry toolbox.

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.

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.

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.

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.

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.

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.

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.

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).

RBPBench is a multi-function tool to evaluate CLIP-seq and other related genomic region data using a comprehensive collection of known RNA-binding protein (RBP) binding motifs. RBPBench can be used for a variety of purposes, from RBP motif search (database or user-supplied RBP motifs) in genomic regions, over motif enrichment and co-occurrence analysis, in-depth comparisons over multiple datasets via sequence and genomic annotation statistics, to benchmarking CLIP-seq peak caller methods as well as comparisons across cell types and CLIP-seq protocols. RBPBench supports both sequence and structure motifs, as well as regular expressions (sequence and structure patterns). Moreover, users can easily provide their own motif collections.

JAMMA (Highly-Accelerated Multi-method Mixed-Model Association) is an open-source Python and C implementation of GEMMA's core linear mixed-model workflows for genome-wide association studies (GWAS). It reads PLINK binary genotypes and supports kinship estimation, Wald, likelihood-ratio and score association tests, covariates, multiple phenotypes, and leave-one-chromosome-out (LOCO) analysis. JAMMA provides a command-line interface with familiar GEMMA flags, GEMMA-compatible association output, and a Python API. Native C kernels, parallel computation and reusable eigendecompositions support large analyses. Pre-flight memory checks and streamed output help manage memory use. Numerical validation against GEMMA is documented. JAMMA runs on Linux, macOS and Windows; large-cohort analyses require sufficient RAM and a suitable 64-bit BLAS configuration. Released under GPL-3.0-or-later.

pyLocusZoom is an open-source Python library for visualizing genome-wide association study (GWAS) results. It creates LocusZoom-style regional association plots with linkage disequilibrium (LD) coloring, gene and exon tracks, and recombination overlays. Additional plots include Manhattan, QQ, Miami, eQTL, fine-mapping credible sets, PheWAS, forest plots, LD heatmaps and colocalization comparisons. Matplotlib provides static figures; Plotly and Bokeh provide interactive views. The library accepts pandas DataFrames and includes loaders for PLINK, GEMMA, REGENIE, BOLT-LMM, SAIGE, GTEx, SuSiE and FINEMAP outputs. It supports canine and feline reference data, automatic Ensembl gene annotations, and custom reference data for other species. LD can be supplied or calculated with PLINK. Requires Python 3.10 or later and is released under GPL-3.0-or-later.

BacSelect is a reproducible resource for selecting compact, nested panels of complete bacterial genome assemblies that span genome architecture. From a defined and versioned public genome universe, BacSelect deterministically selects assemblies so users can choose a panel size from N=10–500 while retaining nestedness across scales. Versioned releases provide genome-panel manifests, downloadable assemblies, structural-coverage information, checksums and provenance for reproducible benchmarking, method development and comparative genomics.

Fits second-order autoregressive AR(2) models to gene expression time series and reports the eigenvalue modulus |lambda|, a single statistic quantifying temporal persistence: how strongly a gene's recent past constrains its next value. Ranks genes into a clock/target/background hierarchy and reports correlation length, half-life and root type (real or complex) per gene.

Predicts transcription factor binding sites in up to 316 vertebrate species by scoring JASPAR matrices against Ensembl promoter sequences and combining the match with seven contextual experimental datapoints, including evolutionary conservation, CAGE-defined transcription start sites, eQTLs, ChIP-seq peaks, ATAC-seq accessibility, DNase footprints and gene expression correlation, into a single score per site.

ReviewAid is an open-source AI-assisted tool for full-text screening and data extraction in systematic reviews. It supports evidence synthesis workflows by using large language models to classify articles according to user-defined PICO criteria and extract structured information from full-text publications. ReviewAid is designed as a supplementary reviewer rather than a replacement for human judgement. It aims to reduce manual workload, improve consistency, and assist researchers during screening and data extraction while maintaining human oversight throughout the evidence synthesis process.

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.

Converts Protein Data Bank structures into 3D-printable models. Each polymer chain is meshed separately and written as a named object in a single 3MF file, so a multi-material printer can assign one filament per chain. Protein chains can be rendered as a solvent-excluded surface, a cartoon, or a backbone tube; nucleic acids as a tube-and-rung form with the strands of a duplex welded at every base pair. Press-fit magnet pockets are optionally placed at chain interfaces, so a complex comes apart where its subunits actually meet. All meshes are checked for watertightness before export.

Noodle is a public, read-only web application for semantic discovery and exploration of biomedical literature sourced from PubMed, Europe PMC, and OpenAlex. It accepts natural-language research questions and presents ranked publications together with gene, genetic variant, and phenotype views. Publication pages provide provenance, identifiers, source links, indexed concepts, and navigable semantic-neighbourhood graphs. The companion Noodle Biomedical Literature Discovery MCP exposes the same public discovery domain through a read-only, source-linked Model Context Protocol interface with bounded citation and semantic graph traversal. Semantic proximity, citation distance, co-mention, and search rank are discovery signals and do not establish scientific evidence, causality, diagnosis, or treatment.

RAiSD-AI is a tool for training, testing, and deploying Convolutional Neural Networks to detect selective sweeps in genomic data, extending the functionality of the original RAiSD software with machine learning capabilities. It supports SNP data processing, CNN model training with TensorFlow or PyTorch, and genome-wide selective sweep detection.

RejuvenationKit is an open-source Python toolkit for reproducible auditing and analysis of longitudinal preclinical rejuvenation studies. It provides protocol-aware missingness checks, experimental-confounding diagnostics, attrition and analysis-readiness profiling, covariance-aware multichannel change detection, sequential response monitoring, randomized longitudinal inference, visualization, and integrity-tracked report bundles.

GAIn is a platform for annotating genetic variants, genomic positions, and regions with reproducible, declarative pipelines using curated Genomic Resource Repositories.

FAIR EVA: Evaluator, Validator & Advisor has been developed to check the FAIRness level of digital objects from different repositories or data portals. It requires the object identifier (preferably persistent and unique identifier) and the repository to check. It also provides a generic and agnostic way to check digital objects. This software started to be developed within IFCA-Advanced-Computing receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 857647.

From https://anndata.readthedocs.io/en/latest/ "Python package for handling annotated data matrices in memory and on disk, positioned between pandas and xarray."

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.

blue-crab is a tool to convert from ONT POD5 format to the community maintained SLOW5/BLOW5 format. Lossless nanopore pod5 s/blow5 file conversion.

Autonomous ML experimentation for biomedical data.

A structural pharmacology workbench for cognition-related CNS targets, built so that a displayed number must trace to a computation. Runs Boltz-2 locally for structure prediction, validates chemistry with RDKit, enforces a provenance record on every value, and reports eight studies pre-registered under content hashes before any data was seen. Its headline result is negative: designed peptides did not separate from composition-matched shuffles of their own amino acids.

Local Python sequence utilities for nucleotide composition, DNA and RNA reverse complements, NCBI genetic-code translation, six-frame candidate ORF enumeration, and IUPAC motif searches. Computase accepts raw nucleotide strings or one FASTA record and returns structured, bounded results with explicit scientific conventions.

Open-source PyMOL plugin for membrane-aware review of predicted, designed and experimental protein structures. Membrane Visual QC provides planar membrane-relative geometry, residue core/interface classification, hydropathy and ligand-context review, solvent-accessibility context, PDBTM/OPM orientation-source checks, and reproducible batch reporting. It is designed as a review assistant rather than a biological structure validator.

NOS-TLPlot is an open-source tool for visualizing Newcastle–Ottawa Scale (NOS) risk-of-bias assessments in systematic reviews. It converts NOS star ratings into publication-ready traffic-light plots and 12 specialized visualizations, enabling reviewers and readers to interpret study-level risk-of-bias results clearly and reproducibly.

Exact, validated excision of coordinate-defined genomic regions from transposed NEXUS matrices.

linkset-automation is a set of tools to automatically generates CyTargetLinker linksets from different resources, starting with WikiPathways.

EcoliTyper is a revolutionary bioinformatics pipeline that eliminates workflow fragmentation in E. coli genomic surveillance. By integrating nine core analyses into a single automated workflow, EcoliTyper transforms disconnected genomic data into coherent biological narratives with actionable public health intelligence. It is a species-optimized computational pipeline for comprehensive genotyping and surveillance of Escherichia coli, perfect for clinical microbiology, outbreak investigations, and genomic research.

ProSeqGO predicts Gene Ontology (GO) terms for protein sequences using ESM2 embeddings and a trained 1-Dimensional Convolutional Neural Network multi-label classifier. By integrating recent advances in protein language models, ProSeqGO facilitates large-scale, automated functional annotation directly from sequence input, empowering researchers to infer protein function, explore biological mechanisms, and accelerate discovery in genomics and proteomics.

RiSPICE (Rice SNP Prioritization Integrating Chromatin Effects) is a computational framework for prioritizing non-coding rice variants by integrating predicted chromatin effects from a fine-tuned DNA language model.

Rapid & standardized annotation of bacterial genomes, MAGs & plasmids

Python computational framework for analysis of single-molecule FRET data

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.

Documentation Rectangle is an open-source Python package for single-cell-informed cell-type deconvolution of bulk and spatial transcriptomic data. Rectangle presents a novel approach to second-generation deconvolution, characterized by hierarchical signature building for fine-grained cell-type deconvolution, estimation and correction of unknown cellular content, and efficient handling of large-scale single-cell data during signature matrix computation. Rectangle was developed to overcome the current challenges in cell-type deconvolution, providing a robust and accurate methodology while ensuring a low computational profile.