Bilkent University
Department of Computer Engineering


In-silico Methods for Metabolic Engineering


Sanjay Ranka
Distinguished Professor and Chair
Computer and Information Science and Engineering
University of Florida
Gainesville, FL, USA

The goal of metabolic engineering is to change the production amount of specific compounds in a metabolic network to a desirable amount, thus altering the state of a pathway. This is often done by manipulating the expression of a set of genes. Existing computational methods for metabolic engineering can answer the forward queries (i.e., how do the production of compounds change when a given set of genes are manipulated?). For many practical applications, however, it is very important to answer the inverse queries (i.e., what is the best set of genes whose manipulations increase or decrease the production of a given set of compounds to a given amount?).

This inverse problem is a critical yet NP-complete problem even for simplistic pathway models. The size of the solution space represented by all possible subsets of enzymes is exponential. This makes approaches based on exhaustive search impractical beyond a few tens of enzymes.

We will present our work on automated screening algorithms to find such subset of genes that induce the desired state of the metabolism. Our methods have potential applications in heath care, bio-energy, industrial chemicals and materials, drug targets, agriculture, and nutrition.

Bio: Sanjay Ranka is a Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research interests are energy efficient computing, high performance computing, data mining and informatics. Most recently he was the Chief Technology Officer at Paramark where he developed real-time optimization software for optimizing marketing campaigns. Sanjay has also held positions as a tenured faculty positions at Syracuse University and as a researcher/visitor at IBM T.J. Watson Research Labs and Hitachi America Limited. Sanjay earned his Ph.D. (Computer Science) from the University of Minnesota and a B. Tech. in Computer Science from IIT, Kanpur, India. He has coauthored two books: Elements of Neural Networks (MIT Press) and Hypercube Algorithms (Springer Verlag), 200+ journal and refereed conference articles. His recent work has received a student best paper award at ACM-BCB 2010, best paper runner up award at KDD-2009, a nomination for the Robbins Prize for the best paper in journal of Physics in Medicine and Biology for 2008, and a best paper award at ICN 2007. He is a fellow of the IEEE and AAAS, and a member of IFIP Committee on System Modeling and Optimization. He is the associate Editor-in-Chief of the Journal of Parallel and Distributed Computing and an associate editor for IEEE Transactions on Parallel and Distributed Computing, Sustainable Computing: Systems and Informatics, Knowledge and Information Systems, and International Journal of Computing. He is co-general chair for 2011 International Conference on Green Computing and 2011 ACM Health Informatics Symposium.


DATE: 4 April, 2011, Monday @ 14:40