Many articles describing new functions for genes and proteins are published every year. The primary means of putting these large amount of information together is by Gene Ontology (GO), which defines genes/proteins using language terms familiar to researchers. However, while there are many GO resources available for higher organisms, there are none suitable for multiple datasets comparison for bacteria. Here, we used a number of novel computational and bioinformatics strategies to design a user-friendly, reliable and multi-purpose website for GO comparisons of data from different sources. We designed different methods to maneuver and visualize diagrams and incorporated these into easily comprehensible reports. As an example of the robustness of the website, we analyzed multiple gene lists of Streptococcus pneumoniae harvested from various tissues of mice. We show that comparing GO distribution among genes from different samples in this manner can greatly improve understanding of the disease process and biological phenomena. The application is flexible enough to integrate both quantity- and quality-based gene selection strategies, resulting in more accurate identification of genes associated with specific functions from diverse biological sources. Such genes can then be investigated as novel targets for prevention and/or treatment of various diseases.