EDAM is an ontology of data analysis and data management in bio- and other sciences, and science-based applications. It comprises concepts related to analysis, modelling, optimisation, and data life cycle. Targeting usability by diverse users, EDAM's structure is relatively simple, divided into 4 sections: Topic, Operation, Data, and Format.

The code and pretrain models of EDAM-WSSS(Embedded Discriminative Attention Mechanism for Weakly Supervised Semantic Segmentation)

Stand-alone, lightweight, and fast JavaScript browser for EDAM and other ontologies

💥 The multifunctional scaffold generator.

Dynamic visualization of softwares managed by a Bioinformatics Core Facility

A Firefox & Chrome extension that displays detailed information about EDAM concepts

EDAMannot is a command-line toolbox which applies to annotations related to the EDAM ontology.

Ideas and code snippets for Elixir Biohackathon 2024 project 27

Agent-first Python CLI for the Evernote Cloud API (EDAM) — JSON output and explicit error codes, built for AI agents and humans.

Slides, swings, and sandbox ontology

Ground truth dataset of bioinformatics software, including 44 analyzed tools. The annotations are compared with those in bio.tools using the EDAM ontology. The dataset covers seven scientific fields: metagenomics, neuroimaging, phylogenetics, single-cell biology, systems biology, genetic variants, and microscopy.

Assessing bioinformatics software annotations: bio.tools case-study

Communities dump their resource/software information, and have them merged

edam-vendor