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.
Filters
Health
Domain
Language(1)
License(1)
Source(1)
Type
20 of 5,923 resources
Deep probabilistic framework for single-cell and spatial omics analysis, integrating scVI, scANVI, totalVI and other VAE-based models for batch correction, cell annotation, multi-omics integration, and RNA velocity (scverse/NumFOCUS, Nature Methods 2018/2024)
Official Jupyter extension with `%%ai` magic commands and sidebar chat assistant, connecting multiple model providers and local inference
Deep learning software to decode EEG, ECG or MEG signals, providing standardized neural network models, preprocessing pipelines, and evaluation workflows for brain-computer interfaces and cognitive neuroscience research (1.2K+ stars, BSD 3-Clause, actively maintained)
Fast, interactive, multi-dimensional image viewer for Python, foundational platform for scientific imaging AI with a rich plugin ecosystem integrating deep learning segmentation, object tracking, and microscopy analysis workflows (2.6K+ stars)
SSSOM is a Simple Standard for Sharing Ontological Mappings, providing - a TSV-based representation for ontology term mappings - a comprehensive set of standard metadata elements to describe mappings and - a standard translation between the TSV and the Web Ontology Language (OWL). Most metadata elements, such as "sssom:mapping_justification" are defined in the sssom namespace.
Generalist deep learning algorithm for cell and nucleus segmentation across diverse image types, with human-in-the-loop training (2.0) and one-click image restoration (3.0), 70K+ training objects (Nature Methods 2021/2022/2025)
Machine learning and statistical learning for neuroimaging in Python, providing easy-to-use tools for fMRI and MRI analysis including decoding, connectivity estimation, and parcellation with seamless scikit-learn integration (INRIA Parietal team, 1.4K+ stars)
The Chromosome Ontology is an automatically derived ontology of chromosomes and chromosome parts.
Probabilistic framework for inferring cell fate decisions and trajectory dynamics from multi-view single-cell data using Markov chains and machine learning, integrating RNA velocity, pseudotime, and metabolic labeling to predict differentiation paths and terminal states (scverse/Theis Lab, 449+ stars, BSD 3-Clause)
ChemML is a machine learning and informatics program suite for the analysis, mining, and modeling of chemical and materials data. (based on Tensorflow)
Manipulation and analysis of geometric objects.
DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.
Deep learning-based variant caller
A library containing basis sets for use in quantum chemistry calculations. In addition, this library has functionality for manipulation of basis set data.
Deep learning-based object detection and segmentation for star-convex shapes, widely adopted for cell and nucleus segmentation in fluorescence and electron microscopy via a compact neural network architecture with non-maximum suppression and shape-based post-processing (Nature Methods 2020, 1.2K+ stars)
A package for working with nuclear magnetic resonance (NMR) data including functions for reading common binary file formats and processing NMR data.
A module for solving and visualizing the Schrödinger equation.
Open Drug Discovery Toolkit, a modular and comprehensive toolkit for use in cheminformatics, molecular modeling etc.