As PubMed grows, literature searches become more complex and time-consuming. Automated search tools with good precision and recall are thus necessary. We developed GO2PUB to address this demand. Our goal was to use the knowledge from Gene Ontology (GO), its annotations and following the true path rule for semantic expansion. GO2PUB enriches PubMed queries based on selected GO terms and keywords. It processes the result and displays the PMID, title, authors, abstract and bibliographic references of the articles. Gene names, symbols and synonyms that have been generated as extra keywords from the GO terms are also highlighted. Two experts manually assessed the relevance of GO2PUB, GoPubMed and PubMed on three queries about lipid metabolism. Experts agreement was high (kappa=0.83). GO2PUB returned 76 % of the relevant articles, GoPubMed: 45 % and PubMed: 21 %. 39 % of the relevant articles were returned only by GO2PUB, and 18 % only by GoPubMed. We also generated 20 queries based on random GO terms with a granularity similar to those of the first three queries and compared the proportions of GO2PUB and GoPubMed results. These were respectively of 70 % and 38 %. The comparison of GO2PUB, based on semantic expansion, with GoPubMed, based on text-mining techniques, showed that both tools are complementary. GO2PUB is available at http://go2pub.genouest.org