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Computational Functional Genomics, Spring 2005

(Complete Item Description)

Abstract:: Study and discussion of computational approaches and algorithms for contemporary problems in functional genomics. Topics include DNA chip design, experimental data normalization, expression data representation standards, proteomics, gene clustering, self-organizing maps, Boolean networks, statistical graph models, Bayesian network models, continuous dynamic models, statistical metrics for model validation, model elaboration, experiment planning, and the computational complexity of functional genomics problems.

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

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Top Keywords

Biology Chromatin Computer Sciences Diagnostic DNA Electrical Engineering Error Model Gene Clustering Gene Expression Gene Sequence Genome Structure Genomic Sequence Microarray Motif Phenotype Protein Proteome RNA statistical data analysis Stem Cell Systems Biology transcription

Conditions of Use

No Strings Attached
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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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