A free online text designed to introduce key topics in Bioinformatics with python

Full Spectrum Bioinformatics

Full Spectrum Bioinformatics is a free online text designed to introduce key topics in Bioinformatics using the Python programming language.

The text is currently in prototype status. Chapters with content you can preview are linked below:

Chapter 1. Foreword
Chapter 2. Introduction
- Exercise: Spot the Difference
Chapter 3. The Command Line
- Using the Command Line
- Exercise: Little Brother is Missing
Chapter 4. Exploring Python
Chapter 5. Project Design
- Using Literature Surveys to Ask Good Questions and Propose Testable Hypotheses
Chapter 6. Biological Sequences
Chapter 7. 'Omics
- An Introduction to 'Omics
- In depth: Characterizing Microbial Community Ecology
- Exercise: Microbiome change scenarios
- Working with Tabular 'Omic data in Python using Pandas
- Analyzing Microbiome Alpha Diversity in Python
- Analyzing Microbiome Beta Diversity in Python
- Simulating the Effect of Sequencing Depth on Diversity Estimates
Chapter 8. Alignment and Phylogenetics
- 8a. Alignment
- Homology and Alignment
- Global Alignment with the Needleman-Wunsch algorithm
- Local Alignment with the Smith-Waterman algorithm
- BLAST and the k-mer trick
- 8b. Phylogenetics
- Tree thinking
- Representing Phylogenetic Trees with Python Classes
- Generating Trees Using Birth-Death Models
- Working with Traits on Trees
- Maximum Parsimony Ancestral State Reconstruction
- Hidden State Prediction
- Phylogenetic Comparative Methods
Chapter 9. Visualization
- Graphs as a Visual Language
- Exercise: Anger Tufte
- Representing Correlation
- Representing Distribution
Chapter 10. Simulation
- Simulating the Population Genetics of Natural Selection and Genetic Drift
- Simulating the Evolution of Social Behavior
Chapter 11. Statistics
- Monte Carlo simulation and the Fundamental Unity of Statistical Hypothesis Tests
- Statistical Distributions and Parametric Tests
- Rank Transformations
- Monte Carlo simulation of Effect Size, Sample Size, and Significance
- Dealing with Multiple Comparisons
- Exercise: Revising your writing about statistical results
- An Introduction to Maximum Likelihood optimization
- The Best Model of A Cat is a Cat - model complexity, overfitting, and the AIC
- An Introduction to Bayesian Approaches
Chapter 12. Multivariate Statistics and Machine Learning
- Of PCoA and Fishtanks
- Supervised and Unsupervised Classification
- K-means clustering
- LDA and the Kernel Trick
- Random Forest Analysis
Chapter 13. Presenting Research
- Presentations as Verbal Chess
Chapter 14. Polishing and Publishing
- Presenting Research
- From Data to Conclusion: building a research manuscript brick by brick
- Resistance is Futile: becoming a language Borg
- Exercise: generating a targeted title using templating
- The Inverted Pyramid: optimizing your text from a reader's perspective
Chapter 15. Careers that draw on Bioinformatics
- Fighting for an Inclusive Workplace
  - Examining Privilege and Identity
  - Making Your Science and Teaching Accessible and Inclusive
  - Campus and Local Activism
  - Improving University Policy
- Happiness Matters
- Radical Collaboration
- Cognitive Bias and Networking
- Open-source Science as Shield and Sword
- Applying for Grants
Appendices:
- Appendix A - Data Sources for Bioinformatics Projects
- Appendix B - Timesaving Starter Code
  - Template Script with Interface and Test Code
  - IUPAC codes in python
  - Standard Translation Tables in Python
- Appendix C - Contributing a Community Example
- Appendix D - Paper Formatting Kit
- Appendix E - Project Specifications