Computational Techniques and Systems For Metabolomics Analysis
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Computational Techniques and Systems For Metabolomics Analysis

A. Ercument Cicek

Case Western Reserve University


Metabolomics is a relatively new “omics” platform, which measures and analyzes a discreet set of small molecules (metabolites) detected in bio-fluids or tissue samples of organisms. Life scientists hypothesize about under-the-hood mechanisms of drug or disease related changes using metabolite measurements over the associated metabolic network of the organism. Given the high number of observations and complex relationships among metabolites, metabolomics analysis is a challenging task with a large search space. Therefore, efficient algorithms and user-friendly computer systems that embrace biochemical principles and guide life scientists through the hypothesis generation stage are needed. In this talk, I will describe two algorithms that serve this purpose. (1) Steady-State Metabolic Network Dynamics Analysis (SMDA) Algorithm that generates possible activation scenarios of the metabolic network, and (2) Algorithm to DEtermine Metabolic Alterations (ADEMA) that computes disease specific metabolic signatures given the metabolite measurements of the control and the variable groups. I will also make a demo on our metabolomics analysis systems: PathCaseMAW and PathCaseRECON, which are available online at


A. Ercument Cicek earned his B.Sc and M.Sc degrees in Computer Science and Engineering program at Sabanci University, in 2007 and 2009 respectively. He also worked as a visiting scholar at University of Texas at Dallas in 2008.  He has been awarded with Fulbright Doctorate Scholarship to seek a Ph.D degree overseas. Currently, Ercument is a research assistant and a Ph.D candidate in Electrical Engineering and Computer Science Department of Case Western Reserve University. He is affiliated as a researcher with the Cystic Fibrosis Research Center in School of Medicine, Case Western Reserve University. He has been awarded with Choose Ohio First scholarship in 2011.

His research is focused on metabolomics, biochemical pathway analysis, and online biological pathway databases/systems.