DIMACS Computational and Mathematical Epidemiology Seminar Series

Title: A Novel Method for Characterizing and Classifying Dissipative Structures in the Transcriptomics of Budding Yeast: Potential Applications to Genomics, Proteomics, Metabonomics, and 'Cytomics'

Speaker: Sungchul Ji, Rutgers University

Date: September 25, 2006 12:00 - 1:30 pm

Location: DIMACS Center, CoRE Bldg, Room 431, Rutgers University, Busch Campus, Piscataway, NJ


In many areas of biology and medicine where the appearance and disappearance of molecules, cells and populations of individual cells and multicellular systems play essential roles, dissipative structures (defined as spatiotemporally organized physicochemical processes that require a continuous dissipation of free energy for their maintenance) appear to be required as the mediators of genotype-phenotype coupling. However, due to the relative novelty of these dynamic and transient structures and the lack of a convenient language to represent them, biomedical scientists have rarely utilized the concept of dissipative structures in their research and by default relied mainly on the concept of equilibrium structures, those structures that can exist without any expenditure of free energy. To help correct this unsatisfactory situation, we need a new language to describe and analyze dissipative structures. In the course of analyzing the genome-wide expression data measured with DNA arrays in budding yeast, we have been led to develop a simple semi-quantitative language that can be used to describe the kinetics of mRNA level changes that occur in yeast during the nutritional stress induced by glucose-galactose shift. This language consists of a six-letter alphabet, each letter representing a mechanism (expressed by a differential equation) of controlling the level of mRNA molecules coded by a gene by modulating their appearance (or production) and disappearance (or degradation). These letters can be combined to form 'words' representing dynamic processes, which in turn can be combined to form 'sentences' to represent sequences of linked processes. We will present examples of all these 'molecular-linguistic' representations of dynamic processes that have been observed in budding yeast during glucose-galactose shift. In addition, we will discuss the possibility of extending these results from the yeast transcriptomics (i.e., the study of genome-wide transcription) to the studies of other dynamic systems such as genomics, proteomics, metabonomics, and 'cytomics'. 'Cytomics' is a new term coined to indicate the study of biological systems constructed out of cells as basic building blocks, including cells themselves, organs, and populations of cells and multicellular systems. 'Cytomics', so defined, appears to provide a novel perspective for integrating molecular, cell, and population biology within a common theoretical framework. It will be pointed out, for example, that the Lotka-Volterra equations in population biology can be viewed as special cases of the differential equation used to express the rate of change of mRNA molecules in yeast cells.

Joint work with Nina Fefferman, and Art Chaovalitwongse, Rutgers University

see: DIMACS Computational and Mathematical Epidemiology Seminar Series 2006 - 2007