A Unified Computational Model of Gene Regulation

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Understanding how instructions stored in DNA are interpreted differently to generate diverse cellular activities is one of the most fundamental, unsolved problems of our time. This "software of life" would explain relationships between different individuals, offspring and species. It would tell us how genetic mutations lead to changes in phenotype or disease. It would offer predictions of the effects of biomolecular disease treatments. It would help us understand, at the cellular level, who we are.Recently, a consortium of thousands of genome researchers from across the globe identified a huge number of DNA elements that appear to be important for controlling activities within cells (ENCODE, 2012). We now now that up to 80% of the human genome contains these important DNA elements, but knowing that something is important is not the same as understanding how it works. This is the topic of our research project. In this project, our goal is to build a "regulatory model" that explains how DNA elements combine together to control the genetic messages (mRNAs) that cells use to control most activites. Several research groups, including mine, have been studying this problem for the past 10 years, but progress has been difficult. While we now have many massive datasets that profile genomes and their genetic messages, we lack good computational models that can effectively combine DNA features with descriptions of cellular conditions to predict genetic messages. We will investigate a novel computational model that unifies and generalize previous work, that helps us understand testable biological mechanisms, that can be used to predict levels of genetic messages for novel genes and cell states, and that is based on well-defined, testable principles. While this is a high risk project, the potential impact is tremendous and our preliminary results indicate that there is good reason to believe we will succeed.