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Extrapolation based Molecular Systems Biology is the utilization of molecular data from one or many sub-cellular levels to indirectly infer the remaining components of a sub-cellular system via statistical algorithms and priori biological knowledge. The motivation to rebuild remaining components of a system is driven primarily by adopting a systems biologist's view of a biological phenomenon where a pan-omic view is a consistent requirement (... Denis Noble "The Music of Life"). The term "extrapolation" is chosen to provide caution due to a high potential of false positives with high levels of extrapolation. On average, fewer levels (and smaller leaps) of inference and greater levels of observational data is recommended for a statistically significant extrapolated system. Sub-cellular levels may include one or more of the following (but not limited to) (see Systems Biology): Genomics, Epigenomics / Epigenetics, Transcriptomics, Interferomics, Translatomics / Proteomics, Metabolomics, Glycomics, Lipidomics, Interactomics, and Fluxomics. thumb Example (see image on right): Molecular level of quantitative data is illustrated in green, inferred levels are illustrated in yellow, and non-active/missing molecular levels are illustrated in grey. Data source(s) & Algorithm(s) are listed on the right. Acknowledgements:Irizarry et al. 2004, Su et al. 2004, Subramanium et al. 2005, Warren et al. 2008, Theocharidis et al. 2009. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Extrapolation based molecular systems biology」の詳細全文を読む スポンサード リンク
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