Dong W, Tang X, Yu Y, Griffith J, Nilsen R, Choi D, Baldwin J, Hilton L, Kelps K, Mcguire J, Morgan R, Smith M, Case M, Arnold J, Schüttler H B, Wang Q, Liu J, Reeves J, Logan D
Genetics Department, University of Georgia, Athens, GA 30602, USA.
IET Syst Biol. 2007 Sep;1(5):257-65. doi: 10.1049/iet-syb:20060080.
A major challenge of systems biology is explaining complex traits, such as the biological clock, in terms of the kinetics of macromolecules. The clock poses at least four challenges for systems biology: (i) identifying the genetic network to explain the clock mechanism quantitatively; (ii) specifying the clock's functional connection to a thousand or more genes and their products in the genome; (iii) explaining the clock's response to light and other environmental cues; and (iv) explaining how the clock's genetic network evolves. Here, the authors illustrate an approach to these problems by fitting an ensemble of genetic networks to microarray data derived from oligonucleotide arrays with approximately all 11 000 Neurospora crassa genes represented. A promising genetic network for the clock mechanism is identified.
系统生物学面临的一个主要挑战是根据大分子的动力学来解释复杂性状，比如生物钟。生物钟给系统生物学带来了至少四个挑战：（i）识别遗传网络以定量解释生物钟机制；（ii）明确生物钟与基因组中上千个或更多基因及其产物的功能联系；（iii）解释生物钟对光和其他环境信号的响应；以及（iv）解释生物钟的遗传网络是如何演化的。在此，作者通过将一组遗传网络与从寡核苷酸阵列获得的微阵列数据进行拟合来说明解决这些问题的一种方法，该寡核苷酸阵列中大约涵盖了粗糙脉孢菌的所有11000个基因。他们识别出了一个很有前景的生物钟机制遗传网络。
