Title of the Talk 

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In-silico methods for Metabolic Engineering

Speaker 

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Abstract

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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.