GOSemSim

GOSemSim computes semantic similarity between GO terms, gene products, and gene sets to quantify functional relatedness using Gene Ontology annotations.

Key Features:

• Semantic similarity algorithms: Implements four information content (IC)-based methods and a graph-based method for calculating semantic similarities among GO terms, sets of GO terms, gene products, and gene clusters.
• Comparison scope: Computes similarity at the level of individual GO terms, term sets, gene products, and gene clusters for flexible analytical comparisons.
• Multi-species support: Supports GO-based comparisons for humans, rats, mice, flies, and yeast.

Scientific Applications:

• Gene function prediction: Predicts gene function by identifying genes with similar GO annotation profiles.
• Functional annotation of genes: Assigns putative functions to uncharacterized genes through similarity to annotated genes based on GO terms.
• Comparative genomics: Enables cross-species functional comparisons using supported organism GO annotations to explore conserved functions and evolutionary relationships.
• Network analysis: Assesses functional similarity among interacting proteins or genes to support analysis of gene and protein networks.

Methodology:

Applies four IC-based algorithms that leverage GO term information content derived from the GO hierarchy and a graph-based method that uses ontology term relationships to compute semantic similarity.