Date: Friday, 28 October 2011
Time: 3 – 4.30 pm
Venue: Lecture Room 3, Nanyang Executive Centre (L3)
Address: 60 Nanyang View, S639673
Speaker: Rohan Williams, Research Leader, Systems Biology, Singapore Centre on Environmental Life Sciences Engineering (SCELSE)
Title: Complex Systems Approaches To Global Gene Expression In Natural And Engineered Environments
The notion that living systems, be they cells, organisms or populations, can be thought of as complex systems appears self evident. I will start by reviewing the concept that genes are the “parts” of such complex living systems, and will review some of the basic concepts behind genes and their functional products (RNA, proteins). Our approach to studying the form and function of genes has rapidly developed in the past decade as a result of new tools available from the field of whole genome sequencing, and I will briefly review these important technologies and some of the strengths and weaknesses of the new kinds of analyses that arisen from them (an emerging field collectively referred to “molecular systems biology”). Finally, I will focus on some of new challenges in trying to develop integrated approaches to studying the biology of natural and engineered environmental systems using these new methods.
Rohan Williams completed undergraduate studies in physics at the University of Technology, Sydney, and then worked in clinical physiology and biomedical engineering, obtaining his Ph.D from UNSW in 2003. From 2004 to 2007 he was an NHMRC Peter Doherty Fellow at UNSW, where he redirected his focus to bioinformatics, genetics and computational biology. In 2007, he was appointed an independent Group Leader at the John Curtin School of Medical Research at the Australian National University in Canberra. He relocated to the National University of Singapore in mid 2011, where he is a Principal Investigator in the Singapore Centre on Environmental Life Sciences Engineering (SCELSE). His primary interests are in statistical bioinformatics, transcriptomics and gene expression, biological data analysis and systems level approaches to understanding biological phenomena.