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SUMMARY:A systems-scale dynamic analysis of complex biology systems - Feng
  He (Helmholtz Center for Infection Research\, Germany)
DTSTART:20080711T130000Z
DTEND:20080711T140000Z
UID:TALK12794@talks.cam.ac.uk
CONTACT:Dr Guy-Bart Stan
DESCRIPTION:_All biological processes are achieved through a complicated s
 patial and temporal dynamic regulation of genes (and thereby proteins). Un
 derstanding the dynamics of complex biological systems is thus a fundament
 al but challenging issue. Currently\, the investigation of the dynamics of
  gene regulation in complex biological systems can be mainly divided into 
 two aspects. On the one hand\, attention is focused on recovering biologic
 al molecular network structure from dynamic genome-scale transcript expres
 sion profiles since the current knowledge of the manner in which genes reg
 ulate each other is far from being complete\, even in model organisms. Thi
 s recovering process is called reverse engineering of biological networks.
  We developed a new reverse engineering method\, termed as trend correlati
 on (TC) method to infer functional linkages among genes and the underlying
  biological networks directly from genome-scale time-series expression dat
 a. Following that\, we have demonstrated how to systematically reveal gene
 s involved in the suppressor function of human regulatory T cells and to p
 rovide the corresponding functional network by employing a systems biologi
 cal strategy. On the other hand\, current efforts are directed towards del
 ineating the dynamic phenomena of biological systems and further decipheri
 ng mechanisms and/or principles underlying the complicated dynamic phenome
 na. We proposed a shifted cumulative regulation principle in which multipl
 e regulators quantitatively control the expression of their target genes i
 n the transcription regulatory network. In addition\, a genome-scale netwo
 rk-based analysis strategy is proposed to identify molecular responsive ne
 tworks with respect to conditional or pathogenic changes and identify ‘h
 idden’ key regulators. These works may thus provide the basis for reveal
 ing and analyzing a dynamic genome-scale genetic network in order to help 
 our understanding of the complicated dynamic mechanisms that determine maj
 or human diseases._
LOCATION:Cambridge University Engineering Department\, Lecture Room 12
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