FSim: A Novel Functional Similarity Search Algorithm and Tool for Discovering Functionally Related Gene Products

Background. During the analysis of genomics data, it is often required to quantify the functional similarity of genes and their products based on the annotation information from gene ontology (GO) with hierarchical structure. A flexible and user-friendly way to estimate the functional similarity of genes utilizing GO annotation is therefore highly desired. Results. We proposed a novel algorithm using a level coefficient-weighted model to measure the functional similarity of gene products based on multiple ontologies of hierarchical GO annotations. The performance of our algorithm was evaluated and found to be superior to the other tested methods. We implemented the proposed algorithm in a software package, FSim, based on R statistical and computing environment. It can be used to discover functionally related genes for a given gene, group of genes, or set of function terms. Conclusions. FSim is a flexible tool to analyze functional gene groups based on the GO annotation databases.