Transcriptome Data Analysis: Methods and Protocols: 1751 (Methods in Molecular Biology) - Tapa dura

 
9781493977093: Transcriptome Data Analysis: Methods and Protocols: 1751 (Methods in Molecular Biology)
Tapa dura
ISBN 10: 1493977091 ISBN 13: 9781493977093
Editorial: Humana Press, 2018

Sinopsis

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

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

This detailed volume provides comprehensive practical guidance on transcriptome data analysis for a variety of scientific purposes. Beginning with general protocols, the collection moves on to explore protocols for gene characterization analysis with RNA-seq data as well as protocols on several new applications of transcriptome studies. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.


Authoritative and useful, Transcriptome Data Analysis: Methods and Protocols serves as an ideal guide to the expanding purposes of this field of study.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Humana Press
Año de publicación
2018
Idioma
Inglés
ISBN 10 
1493977091
ISBN 13 
9781493977093
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
250
Editor
Wang Yejun, Sun Ming-an
Contacto del fabricante
no disponible
Persona responsable
no disponible

Otras ediciones populares con el mismo título

9781493992645: Transcriptome Data Analysis: Methods and Protocols (Methods in Molecular Biology)

Edición Destacada

ISBN 10:  1493992643 ISBN 13:  9781493992645
Editorial: Humana, 2019
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