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Titlebook: High-Dimensional Data Analysis in Cancer Research; Xiaochun Li,Ronghui Xu Book 2009 Springer-Verlag New York 2009 Bayesian Approaches.High

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書目名稱High-Dimensional Data Analysis in Cancer Research
編輯Xiaochun Li,Ronghui Xu
視頻videohttp://file.papertrans.cn/427/426567/426567.mp4
概述Poses new challenges and calls for scalable solutions to the analysis of such high dimensional data.Present the systematic and analytical approaches and strategies from both biostatistics and bioinfor
叢書名稱Applied Bioinformatics and Biostatistics in Cancer Research
圖書封面Titlebook: High-Dimensional Data Analysis in Cancer Research;  Xiaochun Li,Ronghui Xu Book 2009 Springer-Verlag New York 2009 Bayesian Approaches.High
描述.Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n is much larger than p, the number of variables. The properties of statistical models have been mostly discussed under the assumption of fixed p and infinite n. The advance of biological sciences and technologies has revolutionized the process of investigations of cancer. The biomedical data collection has become more automatic and more extensive. We are in the era of p as a large fraction of n, and even much larger than n. Take proteomics as an example. Although proteomic techniques have been researched and developed for many decades to identify proteins or peptides uniquely associated with a given disease state, until recently this has been mostly a laborious process, carried out one protein at a time. The advent of high throughput proteome-wide technologies such as liquid chromatography-tandem mass spectroscopy make it possible to generate proteomic signatures t
出版日期Book 2009
關(guān)鍵詞Bayesian Approaches; High-Dimensional Biologic data; Laboratory; Microarray; Multivariate Nonparametric
版次1
doihttps://doi.org/10.1007/978-0-387-69765-9
isbn_softcover978-1-4419-2414-8
isbn_ebook978-0-387-69765-9Series ISSN 2363-9644 Series E-ISSN 2363-9652
issn_series 2363-9644
copyrightSpringer-Verlag New York 2009
The information of publication is updating

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On the Role and Potential of High-Dimensional Biologic Data in Cancer Research,
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Ross L. Prenticeably intact, though it blebs and the phospholipids redistribute. The specific translocation of phosphatidylserine to the outer leaflet of the plasma membrane has been shown to play a very important role in the recognition of apoptotic cells by phagocytes (Martin et al., 1995). In addition, other mem
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