Roland Pache is trying to understand complex biological interactions using computer algorithms to hunt for patterns in vast swathes of data. Undergraduate Sophia Hsing-Jung Li is excited by this new field of "systems biology." In this film they meet Tim Hunt, whose prizewinning work on the cell cycle and current research on cancer centres on the behaviour of individual molecules. Will Tim share the students’ enthusiasm for systems biology?




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4 Comments
Add CommentI think systems biology has a lot to offer, but it has to be biologically more realistic. Though the field has been recently championed by scientists from a physical science and/or mathematical background, to look at how genes/proteins interact with each other as a global level has long been an eminent biological question. To make systems biology really useful to biology, it has to transcend beyond the current static simple relational approach. This requires the researchers in this field to be very knowledgeable in biology and skillful in computation and statistics, a really rare combination.
Reply | Report Abuse | Link to thisI think systems biology has a lot to offer, but it has to be biologically more realistic. Though the field has been recently championed by scientists from a physical science and/or mathematical background, to look at how genes/proteins interact with each other as a global level has long been an eminent biological question. To make systems biology really useful to biology, it has to transcend beyond the current static simple relational approach. This requires the researchers in this field to be very knowledgeable in biology and skillful in computation and statistics, a really rare combination.
Reply | Report Abuse | Link to thisIt seems that the one truth revealed is that a dialogue is important in scientific research.
Reply | Report Abuse | Link to thisDr. Hunt's ideas are completely in line with our own, which have led us to develop the EGAN (Exploratory Gene Association Networks) software tool.
Reply | Report Abuse | Link to thisSee http://akt.ucsf.edu/EGAN/
Our goal is to combine the output of computational analysis of -omics data with a knowledge base of gene relationships (protein-protein interactions, literature co-occurrence) and metadata (e.g. pathways, Gene Ontology terms) in an interactive environment that allows the biologist to leverage their own trained understanding of the experiment(s) and the genes/relationships/metadata/literature involved.
Systems biology works best when the biologist can map data onto their own knowledge. This is especially important given the fact that gene function, gene-gene relationships, canonical signaling pathways are all different across cell types, cell perturbations (e.g. disease), haplotypes, epigenome states and species.
Only the simplest experiments/phenomena can be easily explained and extrapolated upon by pure in-silico models.