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Titlebook: Bioinformatics and Computational Biology Solutions Using R and Bioconductor; Robert Gentleman,Vincent J. Carey,Sandrine Dudoit Book 2005 S

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樓主: Pierce
11#
發(fā)表于 2025-3-23 10:07:42 | 只看該作者
,Theorie der r?umlichen Kerbwirkung,plotting ordered dissimilarity matrices in R. A new R package hopach, which implements the Hierarchical Ordered Partitioning And Collapsing Hybrid (HOPACH) algorithm, is presented (van der Laan and Pollard, 2003). The methodology is applied to a renal cell cancer gene expression data set.
12#
發(fā)表于 2025-3-23 16:40:33 | 只看該作者
13#
發(fā)表于 2025-3-23 18:02:48 | 只看該作者
SELDI-TOF Mass Spectrometry Protein Data transcriptomics technologies discussed in Chapters 2-4; however, due to the more complicated chemistry of proteins, compared to RNA, the field has a different and diverse set of technologies and produces a wide range of specific challenges. Here we discuss one particular mass spectrometry technology.
14#
發(fā)表于 2025-3-23 22:25:48 | 只看該作者
15#
發(fā)表于 2025-3-24 06:21:30 | 只看該作者
Visualizing Datae dependency between pairs of variables, heatmaps for the visualization of matrix-like data, the visualization of distance relationships between objects, and the visualization of data along genomic coordinates.
16#
發(fā)表于 2025-3-24 08:50:35 | 只看該作者
Analysis Overviewsamples. Most examples are based on microarray data, but the principles are much broader and apply to many other sources of data. In this overview, the basic concepts and assumptions are briefly sketched.
17#
發(fā)表于 2025-3-24 13:02:59 | 只看該作者
18#
發(fā)表于 2025-3-24 15:41:05 | 只看該作者
Ensemble Methods of Computational Inferenceods to data from patients suffering acute lymphoblastic leukemia or renal cell cancer is illustrated. The problem of identifying the best method for a certain prediction task is addressed by means of benchmark experiments.
19#
發(fā)表于 2025-3-24 21:31:57 | 只看該作者
20#
發(fā)表于 2025-3-25 01:24:07 | 只看該作者
https://doi.org/10.1007/978-3-7091-3107-7 all or at least large parts of the experimental procedures and data collection are automated. Cell-based assays offer the potential for clustering of genes based on their functional profiles (Piano et al., 2002) and epistatic analyses to elucidate complex genetic networks (Tong et al., 2004).
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