6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005
This course is offered to both undergraduates and graduates. The undergraduate version of the course includes a midterm and final project. The graduate version of the course includes additional assignments and a more ambitious final project, which can lead to a thesis or publication. Focus will be o...
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| Language: | en-US |
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2005
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| Online Access: | http://hdl.handle.net/1721.1/55901 |
| _version_ | 1811092832499269632 |
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| author | Kellis, Manolis Indyk, Piotr |
| author_facet | Kellis, Manolis Indyk, Piotr |
| author_sort | Kellis, Manolis |
| collection | MIT |
| description | This course is offered to both undergraduates and graduates. The undergraduate version of the course includes a midterm and final project. The graduate version of the course includes additional assignments and a more ambitious final project, which can lead to a thesis or publication. Focus will be on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: Biological Sequence Analysis, Hidden Markov Models, Gene Finding, RNA Folding, Sequence Alignment, Genome Assembly. Networks: Gene Expression Analysis, Regulatory Motifs, Graph Algorithms, Scale-free Networks, Network Motifs, Network Evolution. Evolution: Comparative Genomics, Phylogenetics, Genome Duplication, Genome Rearrangements, Evolutionary Theory, Rapid Evolution. |
| first_indexed | 2024-09-23T15:29:09Z |
| id | mit-1721.1/55901 |
| institution | Massachusetts Institute of Technology |
| language | en-US |
| last_indexed | 2024-09-23T15:29:09Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | mit-1721.1/559012019-09-12T11:04:04Z 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 Computational Biology: Genomes, Networks, Evolution Kellis, Manolis Indyk, Piotr Genomes: Biological sequence analysis hidden Markov models gene finding RNA folding sequence alignment genome assembly Networks: Gene expression analysis regulatory motifs graph algorithms scale-free networks network motifs network evolution Evolution: Comparative genomics phylogenetics genome duplication genome rearrangements evolutionary theory rapid evolution This course is offered to both undergraduates and graduates. The undergraduate version of the course includes a midterm and final project. The graduate version of the course includes additional assignments and a more ambitious final project, which can lead to a thesis or publication. Focus will be on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: Biological Sequence Analysis, Hidden Markov Models, Gene Finding, RNA Folding, Sequence Alignment, Genome Assembly. Networks: Gene Expression Analysis, Regulatory Motifs, Graph Algorithms, Scale-free Networks, Network Motifs, Network Evolution. Evolution: Comparative Genomics, Phylogenetics, Genome Duplication, Genome Rearrangements, Evolutionary Theory, Rapid Evolution. 2005-12 6.895-Fall2005 local: 6.895 local: 6.095J local: IMSCP-MD5-101504e1a71dbb786438e89f55b5d1a4 http://hdl.handle.net/1721.1/55901 en-US Usage Restrictions: This site (c) Massachusetts Institute of Technology 2010. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license") unless otherwise noted. The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. text/html Fall 2005 |
| spellingShingle | Genomes: Biological sequence analysis hidden Markov models gene finding RNA folding sequence alignment genome assembly Networks: Gene expression analysis regulatory motifs graph algorithms scale-free networks network motifs network evolution Evolution: Comparative genomics phylogenetics genome duplication genome rearrangements evolutionary theory rapid evolution Kellis, Manolis Indyk, Piotr 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 |
| title | 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 |
| title_full | 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 |
| title_fullStr | 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 |
| title_full_unstemmed | 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 |
| title_short | 6.895 / 6.095J Computational Biology: Genomes, Networks, Evolution, Fall 2005 |
| title_sort | 6 895 6 095j computational biology genomes networks evolution fall 2005 |
| topic | Genomes: Biological sequence analysis hidden Markov models gene finding RNA folding sequence alignment genome assembly Networks: Gene expression analysis regulatory motifs graph algorithms scale-free networks network motifs network evolution Evolution: Comparative genomics phylogenetics genome duplication genome rearrangements evolutionary theory rapid evolution |
| url | http://hdl.handle.net/1721.1/55901 |
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