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Titlebook: Bioconductor Case Studies; Florian Hahne,Wolfgang Huber,Seth Falcon Book 2008 Springer-Verlag New York 2008 Annotation.Bioinformatics.Clus

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41#
發(fā)表于 2025-3-28 16:09:26 | 只看該作者
Graph Layout,In this chapter we demonstrate how to lay out and render graphs using tools from the . and . packages.
42#
發(fā)表于 2025-3-28 20:59:26 | 只看該作者
43#
發(fā)表于 2025-3-29 00:16:36 | 只看該作者
Michael J?ckel,Jan Dietrich Reinhardtcs, and working with . as hash tables. We introduce the . class as an example for a basic Bioconductor structure used for holding genomic data, in this case expression microarray data. And we explore some visualization techniques for gene expression data to get a feeling for R’s extensive graphical
44#
發(fā)表于 2025-3-29 05:44:36 | 只看該作者
45#
發(fā)表于 2025-3-29 08:16:19 | 只看該作者
https://doi.org/10.1007/978-3-658-43321-5c filtering step to remove probes for genes that appear to be always unexpressed or at least not differentially expressed. Second, a probe-by-probe statistical test, and third, multiple testing correction to get an attenuated test statistic through the false discovery rate (FDR). There are many vari
46#
發(fā)表于 2025-3-29 13:14:52 | 只看該作者
47#
發(fā)表于 2025-3-29 17:15:14 | 只看該作者
https://doi.org/10.1007/978-3-658-22970-2 In this chapter, we explore a curated dataset of protein interactions and perform a statistical analysis of the relationship between protein interaction and coexpression. We also show how to access large-scale protein–protein interaction datasets from the IntAct repository at the EBI.
48#
發(fā)表于 2025-3-29 21:04:00 | 只看該作者
Kreativit?t in der Unterhaltungsproduktion, and it can help to increase the statistical power of analyses by aggregating the signal across groups of related genes. In this chapter, we introduce tools available in the . and . packages for carrying out gene set enrichment analysis.
49#
發(fā)表于 2025-3-30 03:03:21 | 只看該作者
https://doi.org/10.1007/978-3-658-35214-1 functional relationships among those genes that might help better elucidate the underlying biology. These methods typically rely on existing or predefined sets of genes. In this chapter we show how to carry out Hypergeometric tests to identify potentially interesting gene sets.
50#
發(fā)表于 2025-3-30 04:52:16 | 只看該作者
Florian Hahne,Wolfgang Huber,Seth FalconDynamic document: all computations and figures can be reproduced on a local computer.Real data case studies and hands on exercises.Companion website offering color figures and solutions to exercises.I
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