Genomics and Computational Biology | Health Sciences and Technology | MIT OpenCourseWare

Lecture Audio

1A. Intro 1: Computational Side of Computational Biology. Statistics; Perl, Mathematica

1B. Intro 1: Computational Side of Computational Biology. Statistics; Perl, Mathematica

2A. Intro 2: Biological Side of Computational Biology. Comparative Genomics, Models & A...

3A. DNA 1: Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics...

3B. DNA 1 : Genome Sequencing, Polymorphisms, Populations, Statistics, Pharmacogenomics...

4A. DNA 2: Dynamic Programming, Blast, Multi-alignment, Hidden Markov Models

4B. DNA 2: Dynamic Programming, Blast, Multi-alignment, Hidden Markov Models

5AB. RNA 1: Microarrays, Library Sequencing and Quantitation Concepts

5C. RNA 1: Microarrays, Library Sequencing and Quantitation Concepts

6A. RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid ...

6B. RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid ...

7A. Protein 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Fun...

7B. Protein 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Fun...

8A. Protein 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Protein...

8B. Protein 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Protein...

9A. Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods

9B. Networks 1: Systems Biology, Metabolic Kinetic & Flux Balance Optimization Methods

10A. Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks

11A. Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, E...

11B. Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, Ecological & Commercial Models

Course Info

Instructor

Dr. George Church

Departments

Health Sciences and Technology

As Taught In

Fall 2002

Level

Graduate
Undergraduate

Topics

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