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  1. Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis.Jason H. Moore & Scott M. Williams - 2005 - Bioessays 27 (6):637-646.
    Epistasis plays an important role in the genetic architecture of common human diseases and can be viewed from two perspectives, biological and statistical, each derived from and leading to different assumptions and research strategies. Biological epistasis is the result of physical interactions among biomolecules within gene regulatory networks and biochemical pathways in an individual such that the effect of a gene on a phenotype is dependent on one or more other genes. In contrast, statistical epistasis is defined as deviation from (...)
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  • Scale‐free networks in biology: new insights into the fundamentals of evolution?Yuri I. Wolf, Georgy Karev & Eugene V. Koonin - 2002 - Bioessays 24 (2):105-109.
    Scale-free network models describe many natural and social phenomena. In particular, networks of interacting components of a living cell were shown to possess scale-free properties. A recent study(1) compares the system-level properties of metabolic and information networks in 43 archaeal, bacterial and eukaryal species and claims that the scale-free organization of these networks is more conserved during evolution than their content. BioEssays 24:105–109, 2002. Published 2002 Wiley Periodicals, Inc.
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  • Wrestling with pleiotropy: Genomic and topological analysis of the yeast gene expression network.David E. Featherstone & Kendal Broadie - 2002 - Bioessays 24 (3):267-274.
    The vast majority (> 95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized ‘gene expression network’—a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) We find that gene expression interactions form a (...)
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