Find open-source science resources
A directory of tools, AI models, datasets, and research resources for biotech, bioinformatics, and other scientific fields. Aggregated from curated GitHub awesome-lists, HuggingFace, bio.tools, Bioconductor, and more.
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8 of 5,940 resources
A small <720Kb C++ windows utility. That allows you to load Ancestry, 23andMe, FTDNA, or Genes for Good RAW DNA files search them, merge them. covert them to Ancestry format. But also create files from peer reviewed publications to compare with you loaded data to give your genetic disposition for the condition you have entered the data for an statistical risk if OR values are included. Included with the program are example files for Type 2 Diabetes risk factors. (As I have type 2 Diabetes so I could test the results).
AlphaPickle is a Python tool that converts AlphaFold and ColabFold output files into user-friendly CSV files and plots, enabling easy analysis and visualization of protein prediction data without requiring programming expertise. It processes .pkl, .json, and PDB files to extract and visualize metrics like pLDDT and PAE.
NuclearPhaser is a method for phasing of dikaryotic genomes into the two haplotypes using Hi-C contact graphs. This is an overview of the phasing pipeline for dikaryons.
VerityMap is a tool for mapping long reads to assemblies of extra-long tandem repeats, producing SAM files and identifying potential heterozygous sites and assembly errors through analysis of rare k-mers. It supports PacBio HiFi and ONT reads and generates interactive HTML plots for variant analysis.
CompuCell3D is a multiscale multicellular virtual tissue modeling and simulation environment. CompuCell3D is written in C++ and provides Python bindings for model and simulation development in Python.
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.
A comprehensive R package for identifying and ranking influential nodes in biological and other complex networks. The package implements the Integrated Value of Influence (IVI), Experimental data-based Integrative Ranking (ExIR), SIRIR, and numerous network centrality measures, enabling network topology analysis, influential node detection, feature prioritization, and candidate biomarker discovery. It also provides functions for network reconstruction, centrality assessment, visualization, and analysis of relationships between centrality measures.