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Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis http://odin.mdacc.tmc.edu/~llzhang/ RiceCourse

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Page 1: Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis llzhang/RiceCourse

Bioinformatics lectures at Rice University

Li ZhangLecture 9: Networks and integrative genomic

analysishttp://odin.mdacc.tmc.edu/~llzhang/RiceCourse

Page 2: Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis llzhang/RiceCourse
Page 3: Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis llzhang/RiceCourse

Protein-protein interaction networks

Protein-protein interaction network in yeast.Wagner 2001.

Page 4: Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis llzhang/RiceCourse

Power law distribution

Page 5: Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis llzhang/RiceCourse

Gene duplication and divergence

Page 6: Bioinformatics lectures at Rice University Li Zhang Lecture 9: Networks and integrative genomic analysis llzhang/RiceCourse
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P-value of association

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The Method

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Gene set enrichment analysis

Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes).

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MSigDB Collections

C1: positional gene sets

C2: curated gene sets

C3: motif gene sets

C4: computational gene sets

C5: GO gene sets

C6: oncogenic signatures

C7: immunologic signatures

The 10295 gene sets in the Molecular Signatures Database (MSigDB) are divided into 7 major collections, and several sub collections.

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Canonical pathways

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