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Transcriptome analysis = introduction and examples from the neurosciences /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Transcriptome analysis/ by Alessandro Cellerino, Michele Sanguanini.
其他題名:	introduction and examples from the neurosciences /
作者:	Cellerino, Alessandro.
其他作者:	Sanguanini, Michele.
出版者:	Pisa :Scuola Normale Superiore : : 2018.,
面頁冊數:	xiv, 188 p. :digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Bioinformatics. -
電子資源:	http://dx.doi.org/10.1007/978-88-7642-642-1
ISBN:	9788876426421

Transcriptome analysis = introduction and examples from the neurosciences /
Cellerino, Alessandro.

Transcriptome analysisintroduction and examples from the neurosciences /[electronic resource] :by Alessandro Cellerino, Michele Sanguanini. - Pisa :Scuola Normale Superiore :2018. - xiv, 188 p. :digital ;24 cm. - CRM series ;17. - CRM series ;13..

Preface -- Introduction: why study transcriptomics? -- 1. Data distribution and visualisation -- 2. Next-generation RNA sequencing -- 3. RNA-seq raw data processing -- 4. Differentially expressed gene detection & analysis -- 5. Unbiased clustering methods -- 6. Knowledge-based clustering methods -- 7. Network analysis -- 8. Mesoscale transcriptome analysis -- 9. Microscale transcriptome analysis -- Bibliography -- Index.

The goal of this book is to be an accessible guide for undergraduate and graduate students to the new field of data-driven biology. Next-generation sequencing technologies have put genome-scale analysis of gene expression into the standard toolbox of experimental biologists. Yet, biological interpretation of high-dimensional data is made difficult by the lack of a common language between experimental and data scientists. By combining theory with practical examples of how specific tools were used to obtain novel insights in biology, particularly in the neurosciences, the book intends to teach students how to design, analyse, and extract biological knowledge from transcriptome sequencing experiments. Undergraduate and graduate students in biomedical and quantitative sciences will benefit from this text as well as academics untrained in the subject.

ISBN: 9788876426421

Standard No.: 10.1007/978-88-7642-642-1doiSubjects--Topical Terms:

583857
Bioinformatics.

LC Class. No.: QH455 / .C455 2018

Dewey Class. No.: 570.285

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