A Dynamic Biochemical Network Analysis and Gene
Regulation Network Analysis for in vivo biological systems

By

Dr Masa Tsuchiya, Ph.D.
Senior Scientist
Bioinformatics Institute Singapore (BII)

Venue: SBS Classroom 2
Date: 26 April 2005, Tuesday
Time: 3.00 - 4.00 pm

Abstract:
My talk will address two parts: a dynamic biochemical network analysis and gene regulation network analysis for in vivo biological systems. It has been well known that there are fundamental experimental and theoretical difficulties in determining biochemical kinetics including kinetic parameters such as rate coefficients. Recently, Dr. Kumar Selvarajoo and I have succeeded in developing a dynamical network analysis for in vivo metabolic experiments. This dynamical approach is to extract biochemical network connectivity based on perturbation -response experiments. This technique can be applied to uncover the metabolic pathway, genetic network and protein signaling pathway, e.g. to capture potential bio-markers for drug target discovery. As a proof of principle, we have applied the analysis to perturbation-response experiment on in vivo glycolysis pathway in Saccharomyces cerevisiae to predict the actual dynamical network behaviour and network connectivity in metabolic dynamics.

In the second part, I will address a novel cis-regulatory network analysis for P53 auto regulatory feedback loop system. The tumor suppressor p53 is one of the most important genes in maintaining genomic stability and in ensuring the proper elimination of damaged or tumorigenic cells. Some of the key cellular processes controlled by p53 activity include apoptosis, cell cycle arrest, senescence and accelerated DNA repair etc. Due to its critical role in guarding against cancer development, p53 has been the subject of intense research for the past decades. I will discuss sequential logic modeling to elucidate transcriptional control of p53 gene expression and an auto-regulatory feedback loop of p53 by MDM2 protein.

Biodata of Speaker:
Dr. Masa Tsuchiya (theoretical physicist) joined BII as a senior scientist in October 2004. Prior to BII, he has been a senior staff scientist at the Stanford Genome Technology Center and a research assistant professor, Stanford Medical School. Through the years, he has worked on particle physics, quantum chaos, chemical spectroscopy and kinetics, and genomics. In 2002, he has developed novel systematic approaches to understand complex biochemical reaction networks in collaboration with a leading scientist of nonlinear chemistry, Prof. John Ross (Chemistry, Stanford University). He will be an editor of new Journal, “Journal of Systems and Synthetic Biology”, BioMed Central, UK, 2005. His current interest is to understand the dynamics of genetic diseases through the development, modeling and integration of gene regulatory networks and biochemical networks.