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Mathematica for bioinformatics = a W...

Mias, George.

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Mathematica for bioinformatics = a Wolfram language approach to omics /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mathematica for bioinformatics/ by George Mias.
Reminder of title:	a Wolfram language approach to omics /
Author:	Mias, George.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	xvi, 384 p. :ill., digital ;24 cm.
[NT 15003449]:	1 Introduction to Bioinformatics -- 2. A Mathematica Primer for Bioinformaticians -- 3. Statistics for Genomic Analysis -- 4. Genomic Sequences -- 5. Databases -- 6. Transcriptomics -- 7. Proteomics -- 8. Metabolomics -- 9. Systems Biology -- 10. Networks -- 11. Time Series Analysis -- 12. Omics Integration and Systems Medicine -- 13. Bioinformatics Development with Mathematica.
Contained By:	Springer eBooks
Subject:	Life sciences. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-72377-8
ISBN:	9783319723778

Mathematica for bioinformatics = a Wolfram language approach to omics /
Mias, George.

Mathematica for bioinformaticsa Wolfram language approach to omics /[electronic resource] :by George Mias. - Cham :Springer International Publishing :2018. - xvi, 384 p. :ill., digital ;24 cm.

1 Introduction to Bioinformatics -- 2. A Mathematica Primer for Bioinformaticians -- 3. Statistics for Genomic Analysis -- 4. Genomic Sequences -- 5. Databases -- 6. Transcriptomics -- 7. Proteomics -- 8. Metabolomics -- 9. Systems Biology -- 10. Networks -- 11. Time Series Analysis -- 12. Omics Integration and Systems Medicine -- 13. Bioinformatics Development with Mathematica.

This book offers a comprehensive introduction to using Mathematica and the Wolfram Language for Bioinformatics. The chapters build gradually from basic concepts and the introduction of the Wolfram Language and coding paradigms in Mathematica, to detailed worked examples derived from typical research applications using Wolfram Language code. The coding examples range from basic sequence analysis, accessing genomic databases, and differential gene expression, to time series analysis of longitudinal omics experiments, multi-omics integration and building dynamic interactive bioinformatics tools using the Wolfram Language. The topics address the daily bioinformatics needs of a broad audience: experimental users looking to understand and visualize their data, beginner bioinformaticians acquiring coding expertise in providing biological research solutions, and practicing expert bioinformaticians working on omics who wish to expand their toolset to include the Wolfram Language.

ISBN: 9783319723778

Standard No.: 10.1007/978-3-319-72377-8doiSubjects--Topical Terms:

553881
Life sciences.

LC Class. No.: QH324.2 / .M53 2018

Dewey Class. No.: 570.285

Mathematica for bioinformatics = a Wolfram language approach to omics /
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505 0 $a 1 Introduction to Bioinformatics -- 2. A Mathematica Primer for Bioinformaticians -- 3. Statistics for Genomic Analysis -- 4. Genomic Sequences -- 5. Databases -- 6. Transcriptomics -- 7. Proteomics -- 8. Metabolomics -- 9. Systems Biology -- 10. Networks -- 11. Time Series Analysis -- 12. Omics Integration and Systems Medicine -- 13. Bioinformatics Development with Mathematica.
520 $a This book offers a comprehensive introduction to using Mathematica and the Wolfram Language for Bioinformatics. The chapters build gradually from basic concepts and the introduction of the Wolfram Language and coding paradigms in Mathematica, to detailed worked examples derived from typical research applications using Wolfram Language code. The coding examples range from basic sequence analysis, accessing genomic databases, and differential gene expression, to time series analysis of longitudinal omics experiments, multi-omics integration and building dynamic interactive bioinformatics tools using the Wolfram Language. The topics address the daily bioinformatics needs of a broad audience: experimental users looking to understand and visualize their data, beginner bioinformaticians acquiring coding expertise in providing biological research solutions, and practicing expert bioinformaticians working on omics who wish to expand their toolset to include the Wolfram Language.
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