April 6-7, 2017 | Lincoln, Nebraska
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2017 NRIC speakers
portrait of Rajib Saha

 


Dr. Rajib Saha
University of Nebraska-Lincoln
Plant Metabolic Models: from Model Building to ‘Omics’ Data Integration and Answering Important Biological Questions
9:40 - 10:10 am, Friday 7 April 2017
ABSTRACT:
A typical genome-scale metabolic model of a plant (or a plant tissue) contains gene-protein-reaction relationships, elemental and charge-balanced reactions, and incorporates experimental evidence pertaining to the biomass composition, compartmentalization, and flux constraints. Condition-specific biomass descriptions are sometimes introduced that account for amino acids, fatty acids, soluble sugars, proteins, chlorophyll, lignocellulose, and nucleic acids as experimentally measured biomass constituents. Compartmentalization of this sort of model is often based on proteomic/transcriptomic data and literature evidence. Transcriptomic and proteomic data can also be used to introduce regulatory constraints in the model in order to simulate specific environmental and/or genetic conditions. In this talk, we will discuss about the steps of model building, ‘omics’ data integration, and how such models can be useful in answering important biological questions.
BIO:
Rajib Saha is a new assistant professor in the UNL Department of Chemical and Biomolecular Engineering. His research interests include reconstruction and analysis of genome-scale and community models, systems-level analysis of ‘omics’ data, development of genetic toolkit and engineering metabolic pathways, and redesign photosynthetic apparatus and carbon fixing mechanism. Prior to his current appointment he was post-doctoral research associate in the Himadri Pakrasi Lab in Biology department at Washington University in St. Louis. He graduated with his PhD and MS in Chemical Engineering from the Costas Maranas Lab at The Pennsylvania State University in 2014 and 2011, respectively. Prior to that, he earned his bachelor degree in Chemical Engineering from Bangladesh University of Engineering and Technology with the top position in his graduating class. Throughout his multidisciplinary graduate research career, he has developed metabolic network models for photosynthetic organisms and subsequently utilized those for studying their physiology and also for metabolic engineering applications. His recent postdoctoral research includes study of light/dark behavior and development of efficient gene expression control system of a model cyanobacterial strain.