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| 1 | | | | 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. | |
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| 2 | | | | 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). | |
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| 3 | | | | 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.) | |
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| 4 | | | | DNA 2: Dynamic Programming, Blast, Multi-alignment, HiddenMarkovModels. | |
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| 5 | | | | RNA 1: Microarrays, Library Sequencing and Quantitation Concepts.
Note: Problem Set #2 is due. | |
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| 6 | | | | RNA 2: Clustering by Gene or Condition and Other Regulon Data Sources Nucleic Acid Motifs; The Nature of Biological "proofs." | |
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| 7 | | | | Proteins 1: 3D Structural Genomics, Homology, Catalytic and Regulatory Dynamics, Function & Drug Design. | |
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| 8 | | | | Proteins 2: Mass Spectrometry, Post-synthetic Modifications, Quantitation of Proteins, Metabolites, & Interactions. | |
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| 9 | | | | 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.) | |
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| 10 | | | | Networks 2: Molecular Computing, Self-assembly, Genetic Algorithms, Neural Networks. | |
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| 11 | | | | Networks 3: The Future of Computational Biology: Cellular, Developmental, Social, Ecological & Commercial Models. | |
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| 12 | | | | Project Presentations; All written project reports and overhead slides (for presentations) due. | |
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| 13 | | | | Project Presentations. | |
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| 14 | | | | Project Presentations; Problem Set #5 due. | |
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