everything.study
HST.508

Evolutionary and Quantitative Genomics

4-0-8 units · Graduate

Develops deep quantitative understanding of basic forces of evolution, molecular evolution, genetic variations and their dynamics in populations, genetics of complex phenotypes, and genome-wide association studies. Applies these foundational concepts to cutting-edge studies in epigenetics, gene regulation and chromatin; cancer genomics and microbiomes. Modules consist of lectures, journal club discussions of high-impact publications, and guest lectures that provide clinical correlates. Homework assignments and final projects develop practical experience and understanding of genomic data from evolutionary principles.

Fall 2005 · Quantitative Genomics

Topics

  • Introduction - Prof. Leonid Mirny
  • The Basic Forces of Evolution: Mutation, Recombination and Mating, Migration, Neutral Evolution and Drift, Effective Population Size
  • Selection, Fitness, Probability of Fixation, Coalescent Theory
  • Selection, Fitness, and Diffusion Models
  • Human/Mouse/Rat Examples
  • Discussion of Problem Set 1
  • Medical Lecture: Genetic Diversity and Evolution of Hepatitis C Virus - Prof. Isaac Kohane
  • Guest Lecture - Prof. Richard Lewontin
  • Domain Structure of Proteins, Sequence-Structure-Function Relationships
  • Structure of the Genome
  • Infinite Site Model: Nucleotide Diversity, Allele Frequency
  • Multiple Alignments, Profiles and PSSM, HMMs, Domain Databases
  • SNPs: Microevolution, Inference of Population History
  • Recitation: SNPs
  • Medical Lecture: Human Variations Genes, Genotypes and Generations - Dr. Marco Ramoni
  • Overview of Protein Structures, Domain Architecture
  • Structure-based Substitution Matrices
  • Proteomics: Networks of Protein-protein Interactions, Complexes, Modules
  • Proteomics: Evolution of Protein and Regulatory Networks, Function and Misfunction of Genes in Networks
  • Recitation
  • Medical Lecture: Hemoglobin and the Anemias - Prof. Isaac Kohane
  • Guest Lecture
  • Gene Regulation and Function, Conservation, Detecting Regulatory Elements
  • RNA Expression: Clustering and Classification
  • RNA Expression: Classification, 2-way Clustering, Regulatory Modules
  • Dynamics of Biological Networks Metabolic, Regulatory
  • Medical Lectures - Prof. Isaac Kohane Two Examples: Phenylketonuria (monogenic) and Diabetes Type 2 (multigenic+)
  • Final Presentations

Readings

Fall 2002 · Genomics and Computational Biology

Topics

  • Intro 1: Course overview and introduction to the computational side of computational biology. Why use Perl & Mathematica? Write and run simple scripts. We will also assign sections addressing Biology, computing, and advanced topics. Questionaires due.
  • Intro 2: Biological Side of Computational Biology; Central Dogma; Comparative Genomics; Models & Real World Applications. Note: Please take your initial observations about Problem Set#1 to you first section meetings (i.e. check that you actually have access to Perl & Mathematica).
  • DNA 1: Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics; Databases. Note: Problem Set #1 is due at the start of class. (Answers will be posted 48 hrs later.)
  • DNA 2: Dynamic Programming, Blast, Multi-alignment, HiddenMarkovModels.
  • RNA 1: Microarrays, Library Sequencing and Quantitation Concepts. Note: Problem Set #2 is due.
  • RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid Motifs; The Nature of Biological “proofs.”
  • Proteins 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Function & Drug Design.
  • Proteins 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Proteins, Metabolites, & Interactions.
  • Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods. Note: Problem Set #4 is due. (#5 will be available but not due until lecture 14.)
  • Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks.
  • Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, Ecological & Commercial Models.
  • Project Presentations; All written project reports and overhead slides (for presentations) due.
  • Project Presentations.
  • Project Presentations; Problem Set #5 due.

Readings

  • LEC #: 1 · Topics: Intro 1: Course overview and introduction to the computational side of computational biology. Why use Perl & Mathematica? Write and run simple scripts. We will also assign sections addressing Biology, computing, and advanced topics. Questionaires due. · Readings: Mount Chapter 1. Gibas & Jambeck (G&J) Chapters 1, 2, 12 (Those running Unix may find G&J Chaps. 3-5 useful). Students familiar with the above topics should look ahead to next week’s readings.
    Reading assignment
  • LEC #: 2 · Topics: Intro 2: Biological Side of Computational Biology; Central Dogma; Comparative Genomics; Models & Real World Applications Note: Please take your initial observations about Problem Set#1 to you first section meetings (i.e. check that you actually have access to Perl & Mathematica). · Readings: For non-biologists: Primer on molecular biology (PDF) and Molecular Biology for Computer Scientists . ↗
    Reading assignment
  • LEC #: 3 · Topics: DNA 1: Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics; Databases. Note: Problem Set #1 is due at the start of class. (Answers will be posted 48 hrs later.) · Readings: Mount Chap. 2 & 7. G&J Chap. 6, 11, pp. 294-303. Advanced : Pritchard, JK. Are Rare Variants Responsible for Susceptibility to Complex Diseases? Am. J. Hum Gen. 69:124.
    Reading assignment
  • LEC #: 4 · Topics: DNA 2: Dynamic Programming, Blast, Multi-alignment, HiddenMarkovModels. · Readings: Mount Chap. 3. Durbin Chap. 3-5, G&J Chap. 7, 8 (pp. 191-9). Smith T. F., Waterman M. S. “Identification of Common Molecular Subsequences. J Mol Biol 1981 147:195-7.
    Reading assignment
  • LEC #: 5 · Topics: RNA 1: Microarrays, Library Sequencing and Quantitation Concepts. Note: Problem Set #2 is due. · Readings: Lockhart and Winzeler. Genomics, Gene Expression and DNA Arrays . Mount Chap. 10. G&J pp. 311-317. Nature 2000 405:827-36.
    Reading assignment
  • LEC #: 6 · Topics: RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid Motifs; The Nature of Biological “proofs”. · Readings: Tavazoie et al. Systematic Determination of Genetic Network Architecture . G&J 1999, pp. 205-214. Nature Genetics 22:281-5.
    Reading assignment
  • LEC #: 7 · Topics: Proteins 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Function & Drug Design. Note: Problem Set #3 is due. · Readings: G&J Chap. 9 pp. 215-29 and Chap. 10. Advanced: Thompson J., et al. “Analysis of Mutations at Residues A2451 and G2447 of 23S rRNA in the Peptidyltransferase Active Site of the 50S Ribosomal Subunit.” PNAS 98, 16 (Jul 31 2001): 9002-9007.
    Reading assignment
  • LEC #: 8 · Topics: Proteins 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Proteins, Metabolites, & Interactions. · Readings: Ideker, et al. Integrated Genomic and Proteomic Analyses of a Systematically Perturbed Metabolic Network . Chap. 11 pp. 321-328. G&J. Science 292:929 (2001).
    Reading assignment
  • LEC #: 9 · Topics: Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods. Note: Problem Set #4 is due. (#5 will be available but not due until after lecture 13.) · Readings: Edwards and Palsson. Metabolic Flux Balance Analysis and the in Silico Analysis of Escherichia Coli K-12 Gene Deletions . BMC Bioinformatics 1, 1 (2000): 1. Jamshidi, N., et al. Dynamic Simulation of the Human Red Blood Cell Metabolic Network . Bioinformatics 2001 Mar;17(3):286-287.
    Reading assignment
  • LEC #: 10 · Topics: Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks. · Readings: Hopfield, J. J. Odor Space and Olfactory Processing: Collective Algorithms and Neural Implementation . PNAS 96, 22 (1999): 12506-12511.
    Reading assignment
  • LEC #: 11 · Topics: Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, Ecological & Commercial Models. · Readings: Bagowski, C. P., and J. E. Ferrell. Bistability in the JNK Cascade . Curr Biol 2001 Aug 7;11(15):1176-1182.
    Reading assignment
  • Tisdall, James. Beginning Perl for Bioinformatics. O’Reilly & Assoc. 2001.
    Recommended
  • Mount, David. Bioinformatics: Sequence and Genome Analysis. CSHL 2001.
    Recommended
  • Hunter, L. (ed.) Molecular Biology for Computer Scientists. Recommended for all non-biologists.
    Recommended
  • Brown, T. A. Genomes . A good biology reference.
    Recommended
  • Durbin, Richard, S. Eddy, A. Krogh, and G. Mitchison. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids . This book covers basic and advanced models for sequence analysis.
    Recommended
  • Weiss, Neil A. Introductory Statistics. 5th ed. Addison-Wesley, 1999.
    Recommended
  • Mathematica 4.2.
    Recommended
  • Gibas, Cynthia, and Per Jambeck. Developing Bioinformatics Computer Skills . O’Reilly, 2001.
    Recommended
  • Walsh, Linda. The Perl CD Bookshelf . O’Reilly. This CD contains 6 “books” that might supplement numerous free resources on the web: General Perl documents & download . ↗
    Recommended

Prerequisites & course information

Same subject as 1.872[J] Prereq: Permission of instructor Acad Year 2027-2028: G (Fall) Acad Year 2028-2029: Not offered 4-0-8 units

Sources