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Computes R1 and T1 maps from MR images, showing the rate and time of longitudinal relaxation. These are key quantitative biomarkers for tissue characterization.

Extracts diffusion-related maps (e.g., ADC, IVIM, Kurtosis) from DWI sequences to evaluate microstructural properties of tissues, commonly used in oncology and neurology.

Tool for calculating R2 maps from T2*-weighted images. These maps reflect tissue relaxation rates and can be used to assess tissue properties and detect abnormalities.

Implemented by GIBI230, this tool is a Docker-based software designed for extracting radiomic features from 3D medical images in NIfTI format using the PyRadiomics library (if DICOM images, the DICOM to NIFTI converter must be run before using this tool). It streamlines the radiomics calculation process by generating a structured CSV file containing all extracted variables from medical images. The dockerized software enables users to configure parameters like filters, bin width, resampling spacing, and normalization settings can be specified. The output radiomic variables provide quantitative information for further analysis in medical imaging research and machine learning applications. Specially important the parameter selection of the band width. For robust and reproducible results, a bin width of 5 is commonly recommended, but it should be adjusted based on image resolution, modality, and noise levels.

This tool extracts perfusion maps from dynamic imaging data (e.g., DCE-MRI) using pharmacokinetic models or semi-quantitative methods. It supports the evaluation of blood flow and tissue vascularity.

The tool is designed to perform radiomics harmonization on large and heterogeneous datasets, where the risk of over-harmonization is present. Instead of directly applying harmonization based on predefined batch labels, the tool first identifies groups of batches that share similar characteristics through clustering of the radiomics data. It then performs harmonization using these cluster-derived labels. The tool allows the harmonization of radiomics variables using two methods: (1) original ComBat (Rabinovic, 2007) method, where each original batch group is considered for the harmonization process and (2) cluster-based ComBat method, where batch groups with similar radiomics characteristics form clusters and the latter are being considered for the harmonization process.

This preprocessing tool is design for 2D digital mammograms in DICOM format. It standardizes and harmonizes images through a configurable pipeline that includes spatial reorientation, pseudo-3D stacking, isotropic resampling, intensity normalization, optional denoising, contrast enhancement, and mask processing (if available).

The tool performs by deep learning an automatic segmentation of the possible neuroblastoma tumours on Contrast Enhanced CT images (CE-CTs). Model architecture is Unet-based with residual operations, atrous dilation convolution and specific batch generator. It applies preprocessing steps as RAS conversion, resizing, z-score normalization, patching; and postprocessing operations. It takes DICOM images as input and generates tumoral masks in DICOM SEG or NIFTI formats.

The tool performs an automatic segmentation of the possible glioblastoma tumours on MRI images and its subregions: necrosis (Intratumoral necrotic core), edema (Peritumoral vasogenic edema), enhancing (Contrast-enhancing tumor region), total (Total tumor including edema and necrosis by a single model) and total-fused (Total tumor fusioning of necrosis+edema+enhancing). It applies preprocessing steps as skull stripping, intra-patient registration, z-score normalization, patching, among others. It takes DICOM images as input and generates tumoral masks in DICOM SEG or NIFTI formats.

The tool performs an automatic segmentation of the possible DIPG tumours on MR images. DIPG (Diffuse Intrinsic Pontine Glioma), or more recently, DMG (Diffuse Midline Glioma) is a H3 K27M–mutant pediatric brainstem cancer detected in T1W and Flair/T2-weighted magnetic resonance images. The tool includes a complete workflow from DICOM images to DICOM seg tumoral masks.

This tool is specifically designed and validated for automated detection and segmentation of neuroblastic tumours in T2-weighted magnetic resonance images (T2-MR) using deep learning. It processes DICOM or NIfTI input data and outputs in NIFTI or DICOM SEG. TRAINING & VALIDATION COHORTS: Initial Development (Veiga-Canuto 2022): -Training: 106 patients, 5-fold CV (median DSC 0.965 ± 0.018). -Internal validation: 26 patients (median DSC 0.918 ± 0.067). -Sources: La Fe (Spain), SIOPEN HR-NBL1/LINES, St. Anna (Austria), Pisa (Italy). -Mean age: 37.6 ± 39.3 months. -Median tumor volume: 116,518 mm³. External Validation (Veiga-Canuto 2023): -300 patients, 535 independent T2 MRI scans (486 at diagnosis, 49 post-chemotherapy). -Performance: median DSC 0.997 (0.944–1.000), 94% successful detection. -Sources: 12 European countries (HR-NBL1/SIOPEN 119, LINES/SIOPEN 107, German Registry 62, others 12). -Heterogeneous data: 1.5T (435), 3T (100); Siemens (318), Philips (109), GE (105), Canon (3).

The tool is designed to perform a customisable image pre-processing to reduce noise and inhomogeneity field effect, thus improving image quality and reproducibility of radiomics features. This tool consists of two independent steps: one for denoising using one of the 5 integrated filters (Bilateral Filter, Anisotropic Diffusion Filter (ADF), Curvature Flow Filter (CFF), SUSAN and Non Local Means (NLM)), and another for the ANTs N4 and another for the ANT's N4 bias correction filter. The parameter configuration of this tool has been optimised for TW1, T2W, DWI and DCE sequences in neuroblastoma (NB) and paediatric brain tumours, but it can also be configured with some of their parameters using a JSON parameter configuration file.

A tool based on artificial intelligence that is able to perform a categorisation of MRI series by using standardized DICOM tags. The categorisation includes the type of sequence (e.g. spin echo, gradient echo), the weighting (e.g. T1W, T2W, DCE, ...), the presence of fat suppression and the detection of non-relevant / junk series (e.g. localizers, calibrations, screenshots...).

Tool that aims to validate visually the chronological order and logical consistency of dates associated with a patient's medical history. It generates a timeline visualization for each patient from an Excel file and highlights rule violations. Status : Containerized

The tool performs a DICOM quality check in terms of correct number of files per sequence, corrupted files, precise directory hierarchy, separated dynamic series merging them, interest series filtering/selection by specific series description lists and diffusion sequence identification by b-values. It applies the desired changes to the dataset and generates a report containing information about the selected sequences, corrupted files, missing files and merged files. Status: Deployed

VIP is a web portal for medical imaging applications. It allows users to access scientific applications as a service (directly through the web browser with no installation required), as well as distributed computing resources in a transparent manner. It exploits the resources available in the biomed virtual organization of the EGI e-infrastructure to offer an open service to researchers worldwide.

Membrane Protein-Lipid Interaction Database. A large-scale experimentally validated dataset of 80685 residue-level lipid contact annotations across 4712 membrane proteins derived from PDB crystal and cryo-EM structures. Provides pre-computed binary contact labels, continuous distance values, sequence-identity-based cluster assignments, and ready-made train-validation-test splits for machine learning.

ekokrati computes habitat connectivity metrics (PC, IIC, EC(PC), dPC and its decomposition into intra-patch, flux and connector components) for habitat patch networks. Users upload polygon data as GeoPackage or shapefile, set species-specific dispersal parameters, and receive patch importance scores and landscape-level indices. Designed for conservation planners, landscape ecologists and environmental consultants. No installation required.

AI scientist framework for autonomous deep research in biological sciences, combining literature analysis agents with data scientist agents to enable iterative scientific discovery through user feedback integration; achieves state-of-the-art performance on BixBench benchmark (48.78% open-answer, 64.39% multiple-choice) outperforming Kepler and GPT-5 (bio-xyz, arXiv 2601.12542, 160+ stars, 2025-2026)

Verbex is a private, on-device Voice-to-ELN iOS app for scientists. It helps researchers capture experiment notes by voice as work happens, organize those notes into scientific sections, and prepare clean, reviewable, ELN-ready scientific records.

The MetaProteomeAnalyzer Cloud (MPA Cloud) is an intuitive, open-source tool for metaproteomics data analysis and interpretation, designed to analyse comprehensive metaproteomics data from tandem mass spectrometry experiments through a web interface.

Open Babel is a chemical toolbox designed to speak the many languages of chemical data.

Molecular Biology Tools is a free browser-based collection of molecular biology utilities for routine sequence analysis, primer design, Sanger sequencing primer planning, cloning setup, and wet-lab calculations. The site includes tools for PCR primer design, Sanger primer design and primer walking, primer binding checks, restriction site analysis, reverse complement generation, ORF and protein translation, codon optimization, ligation calculations, molarity calculations, dilution calculations, and multi-solute solution recipe preparation. The tools run in the browser and are intended for quick experimental planning, without requiring logins or uploading sequences to the server.

Comprehensive set of programs for phylogenetic analyses; available for PC and Mac; source code available for easy compiling in UNIX.

FlavoTyper is a bioinformatics tool that performs in silico serotyping of Flavobacterium psychrophilum genome assemblies.

MONAI Label is an intelligent open source image labeling and learning tool that enables users to create annotated datasets and build AI annotation models for clinical evaluation. MONAI Label enables application developers to build labeling apps in a serverless way, where custom labeling apps are exposed as a service through the MONAI Label Server.

The ProteinsPlus web server aims to support life scientists in working with protein structures. Protein structures are the key to understanding protein function. They are an important resource in many biotechnological application areas from pharmaceutical research to biocatalysis. ProteinsPlus focuses on protein-ligand interactions. The server provides support for the initial steps of dealing with protein structures, namely structure search, quality assessment, and preprocessing. JAMDA enables users to perform an on-the-fly molecular docking of up to five molecules. The poses can then be visualized in 2D (PoseView, PoseEdit). Furthermore, advanced options, such as protein pocket detection (DoGSite), prediction of water molecule positions (WarPP), protein structure ensemble generation (SIENA), prediction of metal coordination (METALizer), the analysis of solvent channels in protein crystals (LifeSoaks), or the categorization of protein-protein-interfaces (HyPPI) are supported.

SeqBench is a browser-based toolkit for DNA, RNA and protein sequence analysis: primer design, restriction digest and cloning simulation, CRISPR guide design, codon optimization, pairwise alignment and plasmid annotation. Supports batch FASTA processing and multi-tool workflow pipelines, and every tool is also exposed as a REST API and MCP server for scripted or agent-driven use. All computation runs client-side in the browser, so input sequences are never uploaded to a server.

regenie is a C++ program for whole genome regression modelling of large genome-wide association studies.

RxDock is a fast and versatile open-source docking program that can be used to dock small molecules against proteins and nucleic acids. It is designed for high-throughput virtual screening (HTVS) campaigns and binding mode prediction studies.

Bin Chicken - recovery of low abundance and taxonomically targeted metagenome assembled genomes (MAGs) through strategic coassembly

Community Terrestrial Systems Model (includes the Community Land Model of CESM)

Thoa is a cloud bioinformatics platform. Write your Nextflow or Snakemake pipeline, point it at your data, and Thoa handles the rest: provisioning VMs (up to 12TB RAM), resolving dependencies, managing execution. No cloud expertise needed. Every job captures its full context:data, software versions, environment, machine specs, as a reproducibility artifact. Share it with a colleague and they can view or re-run the analysis without an account. Key features: AI debugger that fixes environment and dependency issues in real time. Pipeline tracking with per-step telemetry. if step 47 of 200 fails, re-run from there, not from scratch. One-click data sharing without registration. AI-assisted workflow creation from plain English. Free tier available. Starter $35/mo, Pro $109/mo, Team $480/mo. Zero-egress storage. Based in Zug, Switzerland. thoa.io​​​​​​​​​​​​​​​​

URGI (Unit Resources Genomics-Info) is a bioinformatics facility who support various research activities on plants of agronomic and forestry interest for INRAE. The platform has federated with 3 other INRAE ​​bioinformatics platforms to form the BioinfOmics research infrastructure. It is part of the French Institute of Bioinformatics which is the French node of the European infrastructure ELIXIR . URGI is part of the Saclay Plant Science network and of the Graduate School Biosphera . URGI is labeled by GIS IBiSA and is ISO-9001 certified.

Comparative genomics-driven translational research tool.

Multi-agent system for drug-discovery gene target validation. LangGraph agents over an MCP data layer (~26 data sources, ~44 tools) score evidence across six independent lenses (genetics, biology, safety, clinical, commercial, regulatory) into a provenanced dossier. Configurable local/cloud LLM routing with full Langfuse/OTEL traceability.

metagWGS is a workflow dedicated to the analysis of metagenomic data. It allows assembly, taxonomic annotation, and functional annotation of predicted genes. Since release 2.3, binning step with the possibility of cross-alignment is included. It has been developed in collaboration with several CATI BIOS4biol agents. Funded by Antiselfish Project (Labex Ecofect), ExpoMicoPig project (France Futur elevage) and SeqOccIn project (CPER - Occitanie Toulouse / FEDER), ATB_Biofilm funded by PNREST Anses, France genomique (ANR-10-INBS-09-08) and Resalab Ouest.

Browser-based viewer for Sanger sequencing chromatograms in AB1/ABIF and SCF format. Opens .ab1/.abi/.fsa files, shows raw and analysed traces, basecalls, quality values and the ABIF directory, and puts two reads side by side for comparison. Aligns a read against a reference sequence to highlight mismatches. Exports the read as FASTA, FASTQ or ABIF and the chromatogram as a high-resolution image. Runs entirely in the browser — files are never uploaded.

Conspecta is a browser-based research platform that brings microscopy image analysis, flow cytometry, molecular biology, sample tracking, and publication-ready figures into one connected workspace. It replaces the patchwork of disconnected tools most labs assemble, so a lab's data, samples, and results stay linked from experiment to figure with full traceability. Built for imaging-heavy and flow-heavy biology labs, new PIs, and early-stage biotech. Research-focused, not regulated or clinical. Free for individuals. Paid team plans add shared workspaces.

xnattools is a python package with a set of modules for performing various operations on data stored in XNAT servers. The main purpose is to provide one standardized platform for running operations on XNAT servers. The package currently contains four tools that use this platform: dicom to nifty conversion, thumbnail generation from dicom, DICOM header data collection, in bulk downloading of a project.

BioCalculator is a mobile toolkit for biology and laboratory calculations. It consolidates calculators and preparation guides for molecular biology, microbiology, virology, stock solutions, buffers, dilutions, unit conversions, and TCID50 endpoint dilution workflows for students and lab professionals.

Python package for biodatafuse project.

AmsterdamUMCdb is a database of de-identified health data related to tens of thousands of intensive care unit admissions, including demographics, vital signs, laboratory tests and medications.

austraits is an R package for accessing the AusTraits Plant database and working with traits.build databases

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).

Browser-based tool to open almost any sequence file — FASTA, FASTQ, GenBank, EMBL, Swiss-Prot, AB1/ABIF, SCF, Clustal, Stockholm, PHYLIP, NEXUS, MSF, PIR and more — see every sequence inside, pick the ones you want, and save them as FASTA. The format is detected from the file content, not from the extension, so unlabelled or misnamed files still open. Runs entirely in the browser — files are never uploaded.

VigyanLLM is a sovereign, on-premises biomedical AI platform designed for computational biology. It provides autonomous primer design, evaluating melting temperature (Tm) and GC content; CRISPR guide RNA analysis with off-target scoring; BLAST sequence similarity searching; multiple sequence alignment (MSA); and GPU-accelerated molecular docking for drug discovery. Unlike cloud-based SaaS, VigyanLLM deploys via Docker to ensure institutional genomic data sovereignty

AI Agent for Biomedical Research

SciAgentKit is an MCP-native toolkit that connects AI agents to reproducible computational drug-discovery workflows. It integrates established tools for molecular analysis, protein-structure assessment, binding-site detection, molecular docking, molecular dynamics, trajectory analysis and scientific reporting.

Trace4MedicalImageCleaning™ is a tool aimed at automatically detecting and removing text in medical images, with a specific focus on 2D ultrasound and mammography studies.