Gene Ontology (GO) is a large public database which not only provides a set of controlled biological and bio- chemical vocabularies (terms) to describe gene products based upon their functions in the cell, but also contains gene annotation data from heterogeneous data sources. In this paper, using a new method to measure the seman- tic similarity of GO terms, an efficient algorithm is pro- posed to find genes that have similar biological functions with a given gene. An online tool is then implemented to search the top N genes having similar biological functions with a particular gene within the same or cross different species. Furthermore, various performance enhancement techniques are utilized to reduce the user query response time of the online tool. This tool is available at: http://bioinformatics.clemson.edu/G-SESAME/Programs/geneTop1.php .