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Chapters

This textbook is organized into 16 chapters covering 480 concepts.

Chapter Overview

  1. Foundations of Molecular Biology - Introduces bioinformatics as a discipline and covers the core molecular biology concepts that underpin all computational biology work...
  2. Biological Databases - Surveys the major public repositories for biological data including NCBI...
  3. Bioinformatics Data Formats - Covers the standard file formats used throughout bioinformatics pipelines including FASTA...
  4. Graph Theory Fundamentals - Builds a foundation in graph theory covering node and edge types...
  5. Graph Databases and Query Languages - Introduces graph database technologies including Neo4j and Memgraph...
  6. Sequence Alignment and Homology - Covers pairwise and multiple sequence alignment algorithms (Smith-Waterman...
  7. Phylogenetics and Evolutionary Graphs - Explores phylogenetic tree construction methods (neighbor-joining...
  8. Structural Bioinformatics and Molecular Interactions - Examines protein structure levels from primary to quaternary...
  9. Protein-Protein Interaction Networks - Covers experimental PPI detection methods (yeast two-hybrid...
  10. Genome Assembly and Variation Graphs - Introduces genome assembly using de Bruijn graphs...
  11. Transcriptomics and Gene Regulatory Networks - Covers RNA-seq analysis pipelines...
  12. Metabolic Pathway Modeling - Explores metabolic networks as bipartite graphs...
  13. Signaling Networks and Disease Modules - Covers cell signaling cascades as directed graphs...
  14. Biomedical Knowledge Graphs and Ontologies - Introduces Gene Ontology and disease ontologies...
  15. Multi-Omics Integration and Graph Analytics - Covers integration of genomics...
  16. Python Tools and Capstone Projects - Covers the Python bioinformatics ecosystem including Biopython...

How to Use This Textbook

Chapters are sequenced so that prerequisite concepts appear before they are needed. Chapters 1-3 cover foundations, databases, and data formats. Chapters 4-5 introduce graph theory and graph databases that are used throughout the rest of the course. Chapters 6-15 apply these graph concepts to progressively more complex biological domains. Chapter 16 covers Python tools and capstone projects that tie everything together.


Note: Each chapter includes a list of concepts covered. Make sure to complete prerequisites before moving to advanced chapters.