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Systems analysis of cellular networks under uncertainty
Author(s) -
Kaltenbach Hans-Michael,
Dimopoulos Sotiris,
Stelling Jörg
Publication year - 2009
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/j.febslet.2009.10.074
Subject(s) - systems biology , computer science , biological network , data science , complex system , management science , modelling biological systems , focus (optics) , biochemical engineering , computational biology , risk analysis (engineering) , biology , artificial intelligence , engineering , physics , optics , medicine
Besides the often‐quoted complexity of cellular networks, the prevalence of uncertainties about components, interactions, and their quantitative features provides a largely underestimated hallmark of current systems biology. This uncertainty impedes the development of mechanistic mathematical models to achieve a true systems‐level understanding. However, there is increasing evidence that theoretical approaches from diverse scientific domains can extract relevant biological knowledge efficiently, even from poorly characterized biological systems. As a common denominator, the methods focus on structural, rather than more detailed, kinetic network properties. A deeper understanding, better scaling, and the ability to combine the approaches pose formidable challenges for future theory developments.