Applied Statistics for Network Biology by Dehmer M., et al. (eds.)
By Dehmer M., et al. (eds.)
The ebook introduces to the reader a couple of leading edge statistical tools that could e used for the research of genomic, proteomic and metabolomic info units. particularly within the box of structures biology, researchers try to investigate as many information as attainable in a given organic method (such as a telephone or an organ). the proper statistical evaluate of those huge scale facts is necessary for the right kind interpretation and various experimental techniques require varied methods for the statistical research of those info. This ebook is written by means of biostatisticians and mathematicians yet aimed as a helpful advisor for the experimental researcher besides computational biologists who usually lack a suitable historical past in statistical research.
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Extra resources for Applied Statistics for Network Biology
3 Comparison of simulation results with experimental observations for the genetic toggle switch interfaced with the SOS signaling pathway. Numbers of cells with different LacR molecular numbers are based on 1000 simulations and experimental observations in fluorescence signaling are derived from Figure 3(b) in  using the top and right labels. (a) s ¼ 1:3: no cell has high LacR expression level and no MMC was applied in experiments. 9% of cells have high LacR expression levels and 1 ng/ml MMC was applied.
In the multiplicative case, it was shown that small deviations in the transcription rate could lead to large ﬂuctuations in the production of protein and these ﬂuctuations could be used to amplify protein production signiﬁcantly. In addition, similar observations of the genetic switching have been observed in a more detailed model that includes three binding sites and major binding conﬁgurations of both repressor and cro . 12) and parameter values determined by experiments, numerical simulations indicated that bistability did not exist in this system with the given parameter values .
2, e88. P. et al. (2004) Evidence for dynamically organized modularity in the yeast protein–protein interaction network. Nature, 430, 88–93. , and Alon, U. (2002) Network motifs: simple building blocks of complex networks. Science, 298, 824–827. , and Alon, U. (2004) Superfamilies of evolved and designed networks. Science, 303, 1538–1542. L. (2003) Evolutionary conservation of motif constituents in the yeast protein interaction network. Nat. , 35, 176–179. Yu, H. and Gerstein, M. (2006) Genomic analysis of the hierarchical structure of regulatory networks.