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Systems approaches to biology and disease: integrating discovery and hypothesis‐driven paradigms
Author(s) -
Hood Leroy
Publication year - 2010
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.24.1_supplement.182.1
Subject(s) - systems biology , systems medicine , data science , computer science , biological network , personalized medicine , modelling biological systems , computational biology , biology , bioinformatics
The challenge for biology and medicine in the 21st century is the need to deal with its incredible complexity. One powerful way to think of biology is to view it as an informational science requiring systems approaches. This view leads to the conclusion that biological information is captured, mined, integrated by biological networks and finally passed off to molecular machines for execution. Systems approaches are holistic rather than atomistic—and employ both hypothesis‐driven as well as discovery‐driven approaches. Hence the challenge in understanding biological complexity is that of using systems approaches to deciphering the operation of dynamic biological networks across three time scales of life—development, physiological and disease responses. I will focus on our efforts at a systems approach to disease—looking at prion disease in mice. We have just published a study that has taken more than 5 years—that lays out the principles of a systems approach to disease including dealing with the striking signal to noise problems of high throughput biological measurements and biology itself (e.g. polymorphisms). I will also discuss the emerging technologies (measurement and visualization) that will transform medicine over the next 10 years—including next generation DNA sequencing, microfluidic protein chips and single‐cell analyses. It appears that systems medicine, together with pioneering changes such as next‐generation DNA sequencing and blood protein measurements (nanotechnology) and as well as the development of powerful new computational and mathematical tools will transform medicine over the next 5–20 years from its currently reactive state to a mode that is predictive, personalized, preventive and participatory (P4).

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