Back to the biology in systems biology: what can we learn from biomolecular networks?
Genome-scale molecular networks, including protein interaction and gene regulatory networks, have taken centre stage in the investigation of the burgeoning disciplines of systems biology and biocomplexity. What do networks tell us? Some see in networks simply the comprehensive, detailed description of all cellular pathways, others seek in networks simple, higher-order qualities that emerge from the collective action of the individual pathways. This paper discusses networks from an encompassing category of thinking that will hopefully help readers to bridge the gap between these polarised viewpoints. Systems biology so far has emphasised the characterisation of large pathway maps. Now one has to ask: where is the actual biology in 'systems biology'? As structures midway between genome and phenome, and by serving as an 'extended genotype' or an 'elementary phenotype', molecular networks open a new window to the study of evolution and gene function in complex living systems. For the study of evolution, features in network topology offer a novel starting point for addressing the old debate on the relative contributions of natural selection versus intrinsic constraints to a particular trait. To study the function of genes, it is necessary not only to see them in the context of gene networks, but also to reach beyond describing network topology and to embrace the global dynamics of networks that will reveal higher-order, collective behaviour of the interacting genes. This will pave the way to understanding how the complexity of genome-wide molecular networks collapses to produce a robust whole-cell behaviour that manifests as tightly-regulated switching between distinct cell fates - the basis for multicellular life.
Huang
Sui
S
Department of Surgery, Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA. sui.huang@tch.harvard.edu
D000818:Animals; D005075:Biological Evolution; D001695:Biology / Q000379:methods*; D019070:Cell Lineage; D003201:Computers; D016678:Genome; D006801:Humans; D007858:Learning; D008957:Models, Genetic; D010641:Phenotype; D012984:Software; D013597:Systems Analysis; D013598:Systems Theory