Graphical Approaches to Biological Problems


November 6, 2013


Biology has been transformed by new technologies that provide detailed descriptions of the molecular changes that occur in diseases. However, it is difficult to use these data to reveal new therapeutic insights for several reasons. Despite their power, each of these methods still only captures a small fraction of the cellular response. Moreover, when different assays are applied to the same problem, they provide apparently conflicting answers. I will show that network modeling reveals the underlying consistency of the data by identifying small, functionally coherent pathways linking the disparate observations. We have used these methods to analyze how oncogenic mutations alter signaling and transcription and to prioritize experiments aimed at discovering therapeutic targets.


Ernest Fraenkel

Ernest Fraenkel was first introduced to computational biology in high school when the field did not yet have a name. His early experiences with Professor Cyrus Levinthal of Columbia University taught him that biological insights often come from unexpected disciplines. After graduating summa cum laude from Harvard College in Chemistry and Physics he obtained his Ph.D. at MIT in the department of Biology and did post-doctoral work at Harvard. As the field of Systems Biology began to emerge, he established a research group in this area at the Whitehead Institute and then moved to the Department of Biological Engineering at the Massachusetts Institute of Technology. His research group takes a multi-disciplinary approach involving tightly connected computational and experimental methods to uncover the molecular pathways that are altered in cancer, neurodegenerative diseases, and diabetes.