Overview
- Illustrates research applications with detailed, worked out examples
- Provides complete code companion executable in Mathematica notebooks
- Contains complete instructions for users write their own application in the wolfram language
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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, differential gene expression, and machine learning implementations 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 includethe Wolfram Language.
Authors and Affiliations
Bibliographic Information
Book Title: Mathematica for Bioinformatics
Book Subtitle: A Wolfram Language Approach to Omics
Authors: George Mias
DOI: https://doi.org/10.1007/978-3-319-72377-8
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-72376-1Published: 03 April 2018
Softcover ISBN: 978-3-030-10192-3Published: 19 December 2018
eBook ISBN: 978-3-319-72377-8Published: 16 March 2018
Edition Number: 1
Number of Pages: XVI, 384
Number of Illustrations: 19 b/w illustrations, 156 illustrations in colour
Topics: Computer Appl. in Life Sciences, Metabolomics, Microarrays, Systems Biology, Computational Biology/Bioinformatics, Biostatistics