Argot2 (Annotation Retrieval of Genel Ontology Terms) is able to quickly process thousands of sequences for functional inference. The tool exploits a combined approach based on the clustering process of GO terms dependent on their semantic similarities and a weighting scheme which assesses retrieved hits sharing a certain degree of biological features with the sequence to annotate.
GOssTo is a Java based semantic similarity calculator. Bundled in the software are the well-known Resnik, Lin, Jian, simUI, simGRASM similarity measures. It features powerful extension capabilities allowing the user to add as many similarity measures as needed.
A-DaGO-Fun is a python library that provides a comprehensive and customized set of Gene Ontology (GO) based functional analysis tools that exploit the biological knowledge that GO offers in describing genes or groups of genes through the use of GO semantic similarity measures for biological knowledge discovery.
The DaGO-Fun tool is a an integrated set of GO-based functional analysis tools incorporating the large amounts of biological knowledge that GO offers in describing genes or groups of genes.
FastSemSim is a package that implements several semantic similarity measures. It is both a library and an end-user application, featuring an intuitive graphical user interface (GUI). It has been implemented with the aim of being fast, expandable, and easy to use. It allows the user to work with the most updated version of GO database and customizable annotation corpora. It provides a set of logically-organized classes that can be easily exploited to both integrate semantic similarity into different analysis pipelines and extend the library with new measures.
SemanticSimilarity analysis facilitates automated semantic explanation of biological and clinical data annotated by biomedical ontologies. Gene Ontology (GO) becomes one of the most important biomedical ontologies with a set of controlled vocabularies, providing rich semantic annotations for genes and molecular phenotypes for diseases.