Hello,
Please join the eScience Institute Monday, January 28, 4:00 pm in EEB-303. Refreshments will be provided.
John Gennari (UW)
John Gennari, PhD, received his doctorate in Computer Science (in artificial intelligence) in 1990, and has been carrying out research in biomedical informatics since 1994, starting with the Stanford Medical Informatics group. His primary research focus is in knowledge representation and knowledge sharing. John is extensively published in the Biomedical Informatics literature, in application areas as diverse as health care guidelines, biosimulation modeling and cell-signaling pathways. Dr. Gennari joined the BHI faculty in 2002, and began working in synthetic biology in 2009 in collaboration with Herb Sauro.
Versions and Variants: Adopting engineering principles to synthetic biology
Synthetic biology is a unique interdisciplinary field that combines a deep understanding of genome-level biology, a technical ability to manipulate and synthesize genes at the wet bench, and an engineering approach to the design and development of novel constructs. As the field grows and matures, it needs to apply principles from engineering, such as standardization and modularity, to manage complexity. If synthetic biology components were standardized and modular, then researchers could access libraries of reusable components for adaptation and re-use in new designs, accelerating the pace of science. Our research group has worked over the last several years to help develop the Synthetic Biology Open Language (SBOL), a standard for sharing and reusing synthetic biology designs. In this talk, I report on several early successes with this RDF-based standard.
In addition to broad principles such as modularity, we have discovered that day-to-day research in synthetic biology would also benefit from a more specific software engineering idea: Version control management. In collaboration with Herbert Sauro’s lab, we have developed prototype tools for applying version control to the complexities of the wet-bench process of biological construction. Ultimately, we aim to create intelligent CAD tools that allow researchers to not only leverage standards and reusable libraries of components, but also to carry out intelligent component retrieval, error detection, workflow management, and other sorts of decision support for the design and assembly of new biological constructs.
Upcoming Seminars:
* February 13, 4 PM (EE303)
Gary Johnson
Waiting for Exascale
* March 13, 4 PM (EE303)
Carlos Guestrin (UW)
GraphLab: Making Fast Machine Learning on Big Data Accessible to Data Scientists
* April 11, 4 PM (EE303)
Barry Wark (Physion Consulting)
TBD
* May 1, 4 PM (EE303)
Jeff Gardner (UW)
Simulating the Universe on Google’s Exacycle Platform
* May 13, 4 PM (EE303)
Fernando Perez (Berkeley)
TBD