Iterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equations
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2017-05-09
Print Publication Date2017-06
Permanent link to this recordhttp://hdl.handle.net/10754/623640
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AbstractThe rise and growth of Systems Biology following the sequencing of the human genome has been astounding. Early on, an iterative wet-dry methodology was formulated which turned out as a successful approach in deciphering biological complexity. Such type of analysis effectively identified and associated molecular network signatures operative in biological processes across different systems. Yet, it has proven difficult to distinguish between causes and consequences, thus making it challenging to attack medical questions where we require precise causative drug targets and disease mechanisms beyond a web of associated markers. Here we review principal advances with regard to identification of structure, dynamics, control, and design of biological systems, following the structure in the visionary review from 2002 by Dr. Kitano. Yet, here we find that the underlying challenge of finding the governing mechanistic system equations enabling precision medicine remains open thus rendering clinical translation of systems biology arduous. However, stunning advances in raw computational power, generation of high-precision multi-faceted biological data, combined with powerful algorithms hold promise to set the stage for data-driven identification of equations implicating a fundamental understanding of living systems during health and disease.
CitationGomez-Cabrero D, Tegnér J (2017) Iterative Systems Biology for Medicine – Time for advancing from network signature to mechanistic equations. Current Opinion in Systems Biology. Available: http://dx.doi.org/10.1016/j.coisb.2017.05.001.
SponsorsJ.T. was supported by a CERIC (Center of Excellence for Research on Inflammation and Cardiovascular disease) grant, Vetenskapsrådet Medicine and Health (Dnr 2011-3264), Torsten Söderberg Foundation, FP7 STATegra, and AFA Insurance and Stockholm County Council. The authors would like to acknowledge helpful comments from Drs. Narsis Kiani and Saeed Shoiaie.