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Algorithms for Computational Biology, Spring 2005

(Complete Item Description)

Abstract:: This course is offered to undergraduates and addresses several algorithmic challenges in computational biology. The principles of algorithmic design for biological datasets are studied and existing algorithms analyzed for application to real datasets. Topics covered include: biological sequence analysis, gene identification, regulatory motif discovery, genome assembly, genome duplication and rearrangements, evolutionary theory, clustering algorithms, and scale-free networks.

Subject:: Science and Technology
Grade Level:: Post-secondary
Collection:: MIT OpenCourseWare

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Top Keywords

Biological Sequence Analysis Clustering Algorithms Comparative Genomics computer science Electrical Engineering Evolutionary Theory Gene Expression Gene Finding Genome Assembly Genome Duplication Genome Rearrangements Global and Local Sequence Alignment MacHine Learning Applications Motif Discovery RNA Folding Scale-Free Networks

Conditions of Use

No Strings Attached
Remix and Share
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Read the Fine Print

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Your remixing, redistributing, or making derivatives works comes with some restrictions, including how it is shared.

Your redistributing comes with some restrictions. Do not remix or make derivative works.

Copyrighted materials, available under Fair Use and the TEACH Act for US-based educators, or other custom arrangements. Go to the resource provider to see their individual restrictions.

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