Mathematica for Bioinformatics: A Wolfram Language Approach to Omics

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

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 Co

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 Pa

13.2 Creating a Simple Bioinformatics Package

13.3 Dynamics, Manipulate and Interactive Interfaces