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  1. Shadows of complexity: what biological networks reveal about epistasis and pleiotropy.Anna L. Tyler, Folkert W. Asselbergs, Scott M. Williams & Jason H. Moore - 2009 - Bioessays 31 (2):220-227.
    Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene–gene interaction, has also been treated as an exception to the Mendelian one gene–one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. (...)
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  • Evolution of global regulatory networks during a long‐term experiment with Escherichia coli.Nadège Philippe, Estelle Crozat, Richard E. Lenski & Dominique Schneider - 2007 - Bioessays 29 (9):846-860.
    Evolution has shaped all living organisms on Earth, although many details of this process are shrouded in time. However, it is possible to see, with one's own eyes, evolution as it happens by performing experiments in defined laboratory conditions with microbes that have suitably fast generations. The longest‐running microbial evolution experiment was started in 1988, at which time twelve populations were founded by the same strain ofEscherichia coli. Since then, the populations have been serially propagated and have evolved for tens (...)
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  • Revisiting ``scale-free'' networks.Evelyn Fox Keller - 2005 - Bioessays 27 (10):1060-1068.
    Recent observations of power-law distributions in the connectivity of complex networks came as a big surprise to researchers steeped in the tradition of random networks. Even more surprising was the discovery that power-law distributions also characterize many biological and social networks. Many attributed a deep significance to this fact, inferring a “universal architecture” of complex systems. Closer examination, however, challenges the assumptions that (1) such distributions are special and (2) they signify a common architecture, independent of the system's specifics. The (...)
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  • Revisiting “scale-free” networks.Evelyn Fox Keller - 2005 - Bioessays 27 (10):1060-1068.
    Recent observations of power-law distributions in the connectivity of complex networks came as a big surprise to researchers steeped in the tradition of random networks. Even more surprising was the discovery that power-law distributions also characterize many biological and social networks. Many attributed a deep significance to this fact, inferring a “universal architecture” of complex systems. Closer examination, however, challenges the assumptions that (1) such distributions are special and (2) they signify a common architecture, independent of the system's specifics. The (...)
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  • Can a biologist fix a radio?—Or, what I learned while studying apoptosis.Yuri Lazebnik - 2002 - Cancer Cell 2:179-182.
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