Course: Computational and Systems Biology

Instructor: Dr. Ganesh Bagler

Topics covered in the course:

  1. Introduction to Biological Complex Systems:
    • Definition and notion of system and complexity
    • Natural selection and evolution of biological systems
    • Adaptability; Differences in engineered vs. evolved systems
  2. Biological Sequences and Alignment:
    • Biological sequences: DNA, RNA, Protein
    • Sequence Alignment; phylogeny
    • Basics of Dynamic programming
    • Needleman and Wunsch Algorithm
    • Applications of alignment algorithms
  3. Biological Macromolecules: Proteins:
    • Introduction to proteins
    • Basic ingredients, Ramachandran Plot
    • Protein structure, function and folding
    • Protein structure organization
    • Protein folding models
    • First principle and Knowledge-based models
  4. Homology Modeling and Clustering Methods:
    • Basics of protein structure modeling
    • Homology modeling
    • Basics of clustering
    • K-means clustering
  5. Microarray- Data and Analysis:
    • Basics of microarray technique
    • Applications of microarrays
    • Data compilation and analysis
    • Construction of network models from microarray data
  6. Introduction to Graph Theory and Systems Biology:
    • Introduction to graph theory
    • Graph theoretical metrics
    • Application of graph theoretical analysis for biological systems modeling
  7. Systems Biology- Applications:
    • Gene regulatory networks
    • Protein-protein interactomes
    • Anatomical networks

Reference book:

  1. Carl Branden and John Tooze, "Introduction to protein structure", Garland Science (2nd Ed), 1999
  2. Yaneer Bar-Yam, "Dynamics of Complex Systems", Addison-Wesley, Reading (MA), USA, 1997