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MIT HST.508 Genomics and Computational Biology, Fall 2002

5.0 (0)
8 learners

What you'll learn

This course includes

  • 18.3 hours of video
  • Certificate of completion
  • Access on mobile and TV

Course content

1 modules • 21 lessons • 18.3 hours of video

MIT HST.508 Genomics and Computational Biology, Fall 2002

21 lessons • 18.3 hours
  • 1A. Intro 1: Computational Side of Computational Biology. Statistics; Perl, Mathematica01:02:36
  • 1B. Intro 1: Computational Side of Computational Biology. Statistics; Perl, Mathematica48:40
  • 2A. Intro 2: Biological Side of Computational Biology. Comparative Genomics, Models & A...59:10
  • 2B. Intro 2: Biological Side of Computational Biology. Comparative Genomics, Models & A...48:14
  • 3A. DNA 1: Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics...59:31
  • 3B. DNA 1 : Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics...46:46
  • 4A. DNA 2: Dynamic Programming, Blast, Multi-alignment, Hidden Markov Models55:28
  • 4B. DNA 2: Dynamic Programming, Blast, Multi-alignment, Hidden Markov Models50:14
  • 5AB. RNA 1: Microarrays, Library Sequencing and Quantitation Concepts58:45
  • 5C. RNA 1: Microarrays, Library Sequencing and Quantitation Concepts51:42
  • 6A. RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid ...56:43
  • 6B. RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid ...44:47
  • 7A. Protein 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Fun...01:01:49
  • 7B. Protein 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Fun...42:32
  • 8A. Protein 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Protein...57:58
  • 8B. Protein 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Protein...51:30
  • 9A. Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods54:44
  • 9B. Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods46:41
  • 10A. Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks54:06
  • 11B. Networks 3: The Future of Computational Biology: Cellular, Developmental, Social,...31:47
  • 11A. Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, E...01:02:08

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