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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Used for operations in SPARQL, such as ceil() and bound().
A dictionary of named properties and classes for Software Package Data Exchange (SPDX) - an open standard for communicating software bill of material information, including components, licenses, copyrights, and security references. SPDX reduces redundant work by providing a common format for companies and communities to share important data, thereby streamlining and improving compliance. [from homepage]
The Swiss Personalized Health Network is a national infrastructure initiative with the aim to develop, implement, and validate coordinated data infrastructures in order to make health-relevant data interoperable and shareable for research in Switzerland. The sphn RDF schema builds the foundation for all data exchanges within the sphn by integrating semantic information defined in the [sphn dataset](https://sphn.ch/document/sphn-dataset/).
Systems Science of Biological Dynamics database (SSBD:database) is an added-value database for biological dynamics. It provides a rich set of open resources for analyzing quantitative data and microscopy images of biological objects, such as single-molecule, cell, tissue, individual, etc., and software tools for analysis. Quantitative biological data and microscopy images are collected from a variety of species, sources, and methods. These include data obtained from both experiments and computational simulations.
Systems Science of Biological Dynamics database (SSBD:database) is an added-value database for biological dynamics. It provides a rich set of open resources for analyzing quantitative data and microscopy images of biological objects, such as single-molecule, cell, tissue, individual, etc., and software tools for analysis. Quantitative biological data and microscopy images are collected from a variety of species, sources, and methods. These include data obtained from both experiments and computational simulations.
This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports.
This ontology describes system capabilities, operating ranges, and survival ranges. Please report any errors to the W3C Spatial Data on the Web Working Group via the SDW WG Public List public-sdw-wg@w3.org
The pre-IND tracking number for submissions to the FDA
Datasets inside StoreDB at University of Cambridge
File inside StoreDB at University of Cambridge
Study inside StoreDB at University of Cambridge
STRENDA stands for “Standards for Reporting Enzymology Data”. For researchers it is essential to be able to compare, evaluate, interpret and reproduce experimental research results published in the literature and databases. Thus, for enzyme research, the STRENDA Commission has established standards for data reporting with the aim to improve the quality of data published in the scientific literature. [from homepage]
Identifers for natural products isolated or mutasynthesized by bacteria of the genus Streptomyces.
UMLS Semantic Network The Semantic Network consists of (1) a set of broad subject categories, or Semantic Types, that provide a consistent categorization of all concepts represented in the UMLS Metathesaurus, and (2) a set of useful and important relationships, or Semantic Relations, that exist between Semantic Types.
Identifiers for chemicals used as additives
Identifiers for chemicals used as buffers
Interactions are SupraBank's way to collect information about experiments that describe the binding interaction between molecules. The form for creating an interaction enables you to list all experimental conditions. An interaction is similar to an entry in a table in your scientific publication, but providing machine readable comprehensive information. (from homepage)
Identifiers for molecules in SupraBank
Identifiers for chemicals used as solvents in SupraBank
SWAN ontology consists in a collection of ontologies used to create, manage and share scientific knowledge bases.
SWRL enables Horn-like rules to be combined with an OWL knowledge base.
Identifiers for the binding targets of synthetic binding proteins (SBP), describing the specific molecules or complexes that SBPs interact with for their intended applications
Identifiers for synthetic binding protein-target complexes, detailing their components, 3D structures and docking statistics
Identifiers for the protein scaffolds of synthetic binding proteins (SBP), detailing their structural frameworks and roles in facilitating SBP function.