Transcriptome Data Analysis: Methods and Protocols

N/A

ISBN 10: 1493977091 / ISBN 13: 9781493977093

Edité par Humana, 2018

2018. Hardcover. . . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9781493977093

Synopsis :

Part I: General Protocols on Transcriptome Data Analysis

1. Comparison of Gene Expression Profiles in Non-Model Eukaryotic Organisms with RNA-Seq

Han Cheng, Yejun Wang, and Ming-an Sun

2. Microarray Data Analysis for Transcriptome Profiling

Ming-an Sun, Xiaojian Shao, and Yejun Wang

3. Pathway and Network Analysis of Differentially Expressed Genes in Transcriptomes

Qianli Huang, Ming-an Sun, and Ping Yan

4. QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization

Wen He, Shanrong Zhao, Chi Zhang, Michael S. Vincent, and Baohong Zhang

Part II: Objective-Specialized Transcriptome Data Analysis

5. Tracking Alternatively Spliced Isoforms from Long Reads by SpliceHunter

Zheng Kuang and Stefan Canzar

6. RNA-Seq-Based Transcript Structure Analysis with TrBorderExt

Yejun Wang, Ming-an Sun, and Aaron P. White

7. Analysis of RNA Editing Sites from RNA-Seq Data Using GIREMI

Qing Zhang

8. Bioinformatic Analysis of MicroRNA Sequencing Data

Xiaonan Fu and Daoyuan Dong

9. Microarray-Based MicroRNA Expression Data Analysis with Bioconductor

Emilio Mastriani, Rihong Zhai, and Songling Zhu

10. Identification and Expression Analysis of Long Intergenic Non-Coding RNAs

Ming-an Sun, Rihong Zhai, Qing Zhang, and Yejun Wang

11. Analysis of RNA-Seq Data Using TEtranscripts

Ying Jin and Molly Hammell

Part III: New Applications of Transcriptome

12. Computational Analysis of RNA-Protein Interactions via Deep Sequencing

Lei Li, Konrad U. Förstner, and Yanjie Chao

13. Predicting Gene Expression Noise from Gene Expression Variations

Xiaojian Shao and Ming-an Sun

14. A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data

Jinfeng Zou, Daoquan Xiang, Raju Datla, and Edwin Wang

15. Single-Cell Transcriptome Analysis Using SINCERA Pipeline

Minzhe Guo and Yan Xu

16. Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues

Niya Wang, Lulu Chen, and Yue Wang

Détails bibliographiques

Titre : Transcriptome Data Analysis: Methods and ...
Éditeur : Humana
Date d'édition : 2018
Reliure : Couverture rigide
Etat : New