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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
41#
發(fā)表于 2025-3-28 15:41:53 | 只看該作者
42#
發(fā)表于 2025-3-28 19:23:43 | 只看該作者
Cell-Based Assayshe contribution of genes to a biological process or phenotype (Carpenter and Sabatini, 2004). In principle, this can be done for any gene or combination of genes and for any biological process of interest. There is a variety of technologies, but all of them rely on the availability of genomic resour
43#
發(fā)表于 2025-3-29 01:59:37 | 只看該作者
44#
發(fā)表于 2025-3-29 06:23:44 | 只看該作者
45#
發(fā)表于 2025-3-29 08:32:01 | 只看該作者
Querying On-line Resourcesrt the use of different technologies (including HTTP, SOAP, and XML-RPC) for accessing different Web services. In this chapter we describe the tools for accessing Web services and demonstrate their use in a number of examples..Our view is very similar to that proposed by Stein (2002), who emphasized
46#
發(fā)表于 2025-3-29 12:51:50 | 只看該作者
Interactive Outputs-line resources, such as those supplied by the EBI or the NCBI, and which can be shared between different investigators. We discuss both the simple creation of these pages as well as some of the underlying software tools that can be used to construct new and different outputs. Although linked Web pa
47#
發(fā)表于 2025-3-29 16:32:06 | 只看該作者
Visualizing Datascientific papers. Here we review some of the recurring concepts in visualizing genomic and biological data. We discuss scatterplots to investigate the dependency between pairs of variables, heatmaps for the visualization of matrix-like data, the visualization of distance relationships between objec
48#
發(fā)表于 2025-3-29 20:50:30 | 只看該作者
Analysis Overview is that preprocessing has led to a sample for which it is reasonable to make comparisons between samples or between feature-vectors assembled across samples. Most examples are based on microarray data, but the principles are much broader and apply to many other sources of data. In this overview, th
49#
發(fā)表于 2025-3-30 00:25:30 | 只看該作者
Distance Measures in DNA Microarray Data Analysise classified or clustered. Different measures of distance or similarity will lead to different machine learning performance. The appropriateness of a distance measure will typically depend on the types of features being used in the learning process..In this chapter, we examine the properties of dist
50#
發(fā)表于 2025-3-30 04:13:37 | 只看該作者
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