Mathematica for Bioinformatics (eBook)

A Wolfram Language Approach to Omics

George Mias (Autor)

eBook Download: PDF

2018 | 1st ed. 2018
XVI, 384 Seiten
Springer International Publishing (Verlag)
978-3-319-72377-8 (ISBN)

Infos

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 include the Wolfram Language.

Inhalt

1 Introduction to Bioinformatics 1.1 Principles of Genomics 1.2 Beyond the Genomes: Multiple Omics 1.3 Systems and Networks 1.4 Bioinformatics in modern genetics   2. A Mathematica Primer for Bioinformaticians 2.1 Getting Started 2.2 Variables 2.3 Lists 2.4 Functions 2.4 Importing and Exporting Data 2.5 Graphics 2.6 Associations and Query 2.7 Wolfram Alpha 2.8 Wolfram Language Resources   3. Statistics for Genomic Analysis 3.1 Probability 3.2 Distributions 3.3 Hypotheses 3.4 Parametric Testing 3.5 Non-parametric Testing 3.6 Markov Chains 3.7 Exploratory Data Analysis   4. Genomic Sequences 4.1 Sequence Alignments 4.2 Pairwise Alignment 4.3 Dynamic Programming 4.4 Processing Sequencing Files   5. Databases 5.1 Connecting to Databases 5.2 UCSC Browser and MySQL 5.3 Gene Ontology Annotations 5.4 Biological Pathways 5.5 Genomic Medicine Data Sources   6. Transcriptomics 6.1 Transcriptomic Data 6.2 Quality Control 6.3 Normalization 6.4 Differential Gene Expression 6.5 Visualization 6.6 Classification and Biological Significance   7. Proteomics 7.1 Proteomics Data 7.2 Spectral Visualization 7.3 Quality Control 7.4 Normalization 7.5 Differential Protein Expression 7.6 Visualization   8. Metabolomics 8.1 Metabolomics Data 8.2 Metabolomics Databases 8.3 Metabolomics Data Analysis 8.4 Putative Identification of Compounds 8.5 Clustering and Principal Components Analysis   9. Systems Biology 9.1 Introduction to Systems Biology 9.2 Basic Models 9.3 Visualization of Data 9.4 Beyond Basic Models   10. Networks 10.1 Introduction to Network Analysis 10.2 Basic Network Construction 10.3 Network Properties 10.4 Network Comparison 10.5 Scale Free Networks   11. Time Series Analysis 11.1 Introduction to Time Series 11.2 Regularly Sampled Time Series 11.3 Frequency Representation of Longitudinal Data 11.4 Uneven Sampling   12. Omics Integration and Systems Medicine 12.1 Introduction to Multiple Omics Integration 12.2 Systems Medicine Approaches 12.3 Example Integration of Omics Datasets   13. Bioinformatics Development with Mathematica 13.1 Introduction to Packages13.2 Creating a Simple Bioinformatics Package 13.3 Dynamics, Manipulate and Interactive Interfaces  

Produkt-Details

• Erscheint lt. Verlag: 16.3.2018
• Zusatzinfo: XVI, 384 p. 175 illus., 156 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Studium ► 2. Studienabschnitt (Klinik) ► Humangenetik
• Themenwelt: Naturwissenschaften ► Biologie
• Schlagworte: Bioinformatics • Computational Biology • Data Mining • Mathematica • Metabolomics • microarrays • omics technologies • systems biology
• ISBN-10: 3-319-72377-4 / 3319723774
• ISBN-13: 978-3-319-72377-8 / 9783319723778