Biostatistics & Medical Informatics
Faculty Advisor: Mark Craven
Over the past several years, genomics research has increasingly embraced high-throughut experimental technologies such as gene expression microarrays and SNP chips. On the one hand, these technologies allow researchers to easaily obtain thousands of measurements of biological interest. On the other hand, the vastness of the resulting data often makes them difficult to interpret. For example, these technologies have enabled researchers to isolate a large set of S. cerevisiae genes which have a significant modifying effect on viral replication in infected host cells (Kushner et al., PNAS 100(26), 2003). However, trying to elucidate the functional relationships among these genes, and thus gain insight into how they impact the virus as they do, can be a daunting task. I will develop a software system that exploits the primary biomedical literature in assisting genomics researchers with such endeavors.
