Half dozen of one, six billion of the other: What can small- and large-scale molecular systems biology learn from one another?

• Published in: Genome research 2015-10, Vol.25 (10), p.1466-1472
• Main Authors: Mellis, Ian A, Raj, Arjun
• Format: Article
• Language: English
• Subjects: Algorithms; Computational Biology; Genetic Research; Genomics; Humans; Models, Biological; Molecular Biology; Systems Biology
• ISSN: 1088-9051; 1549-5469
• DOI: 10.1101/gr.190579.115

Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines.