The University of California, Santa Cruz, has been awarded a grant to create Multiple Species Gene Recommender, a search engine that scans gene expression datasets across multiple organisms to identify new genes that act in a pathway of interest. The project will provide insights into gene regulation, which will contribute to a fundamental understanding of cell biology and human health. It will also serve as an invaluable instructional tool for training the next generation of scientists. Most genes in the human genome have no currently known function; in addition, our knowledge about which genes play significant roles in well-studied pathways is incomplete, especially in higher organisms. The functional genomics community is amassing data about complex biological systems through the application of high-throughput technologies. It is crucial for the progress of both science and medicine that, in addition to the organization and dissemination of this information, methods for searching these data be developed to further our understanding of genetic pathways. The project will improve our ability to predict gene function in the human genome, as well as provide functional insights for thousands of genes that currently lack characterization. The educational goal of this project is to provide an interdisciplinary experience, where students learn fundamental concepts in developing computational tools for analyzing large collections of functional genomics data. Teaching the next generation of scientists about techniques from ecommerce promises to accelerate scientific discovery. The algorithms developed in this project will provide a valuable teaching tool for computational biology students studying machine learning methods applied to problems in molecular biology. The search-engines developed will be made available as public resources accessible over the internet without restriction.