標(biāo)題: Titlebook: Bioconductor Case Studies; Florian Hahne,Wolfgang Huber,Seth Falcon Book 2008 Springer-Verlag New York 2008 Annotation.Bioinformatics.Clus [打印本頁] 作者: 減輕 時間: 2025-3-21 19:40
書目名稱Bioconductor Case Studies影響因子(影響力)
書目名稱Bioconductor Case Studies影響因子(影響力)學(xué)科排名
書目名稱Bioconductor Case Studies網(wǎng)絡(luò)公開度
書目名稱Bioconductor Case Studies網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Bioconductor Case Studies被引頻次
書目名稱Bioconductor Case Studies被引頻次學(xué)科排名
書目名稱Bioconductor Case Studies年度引用
書目名稱Bioconductor Case Studies年度引用學(xué)科排名
書目名稱Bioconductor Case Studies讀者反饋
書目名稱Bioconductor Case Studies讀者反饋學(xué)科排名
作者: CLOT 時間: 2025-3-21 22:05
Book 2008n spans a broad field of technologies used in contemporary molecular biology. In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Topics covered include: (1) import and preprocessing of data from various sources; (作者: Vaginismus 時間: 2025-3-22 03:49
2197-5736 website offering color figures and solutions to exercises.I.Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. Its application spans a broad field of technologies used in contemporary molecular biology. In this volu作者: myopia 時間: 2025-3-22 04:47 作者: 反省 時間: 2025-3-22 12:21 作者: 向前變橢圓 時間: 2025-3-22 14:45
Alexander V. Steckelberg,Alexander Kielften, it is beneficial to use gene annotation in the course of the primary analysis, in order to narrow down the set of data to be considered and ameliorate multiple testing problems, or in order to explore specific biological hypotheses.作者: 獸群 時間: 2025-3-22 18:23 作者: 創(chuàng)造性 時間: 2025-3-22 21:18 作者: 不吉祥的女人 時間: 2025-3-23 01:22
Annotation and Metadata,ften, it is beneficial to use gene annotation in the course of the primary analysis, in order to narrow down the set of data to be considered and ameliorate multiple testing problems, or in order to explore specific biological hypotheses.作者: 竊喜 時間: 2025-3-23 08:54
2197-5736 re advanced considerations of key topics. The book is a dynamic document. All the code shown can be executed on a local computer, and readers are able to reproduce every computation, figure, and table..978-0-387-77239-4978-0-387-77240-0Series ISSN 2197-5736 Series E-ISSN 2197-5744 作者: 多余 時間: 2025-3-23 12:49
R and Bioconductor Introduction,cs, 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 作者: recede 時間: 2025-3-23 14:28 作者: 雪白 時間: 2025-3-23 19:34
Easy Differential Expression,c 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作者: 玉米棒子 時間: 2025-3-23 23:09
Annotation and Metadata,mapping them to their target genes, one will want to use the annotation of the genes and gene products to better interpret the experimental results. Often, it is beneficial to use gene annotation in the course of the primary analysis, in order to narrow down the set of data to be considered and amel作者: municipality 時間: 2025-3-24 02:37
Using Graphs for Interactome Data, 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.作者: 懶惰人民 時間: 2025-3-24 08:41 作者: 縮短 時間: 2025-3-24 13:23
Hypergeometric Testing Used for Gene Set Enrichment Analysis, 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.作者: Heretical 時間: 2025-3-24 15:26 作者: Hamper 時間: 2025-3-24 20:14
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 capabilities.作者: 反饋 時間: 2025-3-24 23:12
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.作者: 鞏固 時間: 2025-3-25 04:41
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.作者: 柔軟 時間: 2025-3-25 08:57 作者: LAVA 時間: 2025-3-25 13:11 作者: 輕快帶來危險 時間: 2025-3-25 16:16 作者: podiatrist 時間: 2025-3-25 21:38 作者: 信任 時間: 2025-3-26 01:31
Using Graphs for Interactome Data, 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.作者: Felicitous 時間: 2025-3-26 05:26 作者: CRUMB 時間: 2025-3-26 10:30
Hypergeometric Testing Used for Gene Set Enrichment Analysis, 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.作者: A精確的 時間: 2025-3-26 15:10 作者: 擁護者 時間: 2025-3-26 18:51 作者: 注意到 時間: 2025-3-26 21:52 作者: gain631 時間: 2025-3-27 01:36
Kreativit?t im Kontext von New WorkIn this chapter we will cover some of the basic principles of finding differentially expressed genes. We cover nonspecific filtering, multiple testing, the moderated test statistics provided by the . package, and gene selection by ROC curves.作者: ethereal 時間: 2025-3-27 07:21 作者: 喪失 時間: 2025-3-27 11:02
Julia Sophie Haager,Tanja Gabriele BaudsonIn this chapter we demonstrate how to lay out and render graphs using tools from the . and . packages.作者: 細菌等 時間: 2025-3-27 15:44 作者: 法律 時間: 2025-3-27 19:18
The ALL Dataset,In this initial chapter we briefly describe the typical data preprocessing steps for a sample dataset that will be used in many of the following exercises.作者: 離開真充足 時間: 2025-3-28 01:21 作者: 鋼筆尖 時間: 2025-3-28 02:39
Two Color Arrays,In this case study, two RNA samples are compared to each other on 60 mer oligonucleotide microarrays using two-color labeling. The lab covers data import, visualization, exploration and normalization of the data, and the identification of differentially expressed genes.作者: 大炮 時間: 2025-3-28 07:29 作者: Fabric 時間: 2025-3-28 14:11 作者: PHAG 時間: 2025-3-28 16:09
Graph Layout,In this chapter we demonstrate how to lay out and render graphs using tools from the . and . packages.作者: endoscopy 時間: 2025-3-28 20:59 作者: Agility 時間: 2025-3-29 00:16
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 作者: 案發(fā)地點 時間: 2025-3-29 05:44 作者: 陪審團 時間: 2025-3-29 08:16
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作者: antiandrogen 時間: 2025-3-29 13:14 作者: echnic 時間: 2025-3-29 17:15
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.作者: 使習(xí)慣于 時間: 2025-3-29 21:04
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.作者: 農(nóng)學(xué) 時間: 2025-3-30 03:03
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.作者: incredulity 時間: 2025-3-30 04:52
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作者: 修正案 時間: 2025-3-30 08:30 作者: 賞心悅目 時間: 2025-3-30 12:45
ETHER: Energy- and Cost-Efficient Framework for?Seamless Connectivity over?the?Integrated Terrestriarural areas or the harsh propagation conditions due to the terrain. Indicative applications include forestry, mining, agriculture, semi-autonomous control of long-range vehicles, industrial services, logistics, asset tracking, telemedicine, beyond visual-line-of-sight drone operations, and maritime 作者: 大氣層 時間: 2025-3-30 19:10 作者: Fatten 時間: 2025-3-30 22:01
