PoplarV1, Main, Exploration, bibRecord, 000251

Network Modeling of Complex Data Sets.

Identifieur interne : 000251 ( Main/Exploration ); précédent : 000250; suivant : 000252

Network Modeling of Complex Data Sets.

Auteurs : Piet Jones [États-Unis] ; Deborah Weighill [États-Unis] ; Manesh Shah [États-Unis] ; Sharlee Climer [États-Unis] ; Jeremy Schmutz [États-Unis] ; Avinash Sreedasyam [États-Unis] ; Gerald Tuskan [États-Unis] ; Daniel Jacobson [États-Unis]

Source :

Methods in molecular biology (Clifton, N.J.) [ 1940-6029 ] ; 2020.

RBID : pubmed:32720156

Abstract

We demonstrate a selection of network and machine learning techniques useful in the analysis of complex datasets, including 2-way similarity networks, Markov clustering, enrichment statistical networks, FCROS differential analysis, and random forests. We demonstrate each of these techniques on the Populus trichocarpa gene expression atlas.

DOI: 10.1007/978-1-0716-0195-2_15
PubMed: 32720156

Affiliations:

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Le document en format XML

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<front><div type="abstract" xml:lang="en">We demonstrate a selection of network and machine learning techniques useful in the analysis of complex datasets, including 2-way similarity networks, Markov clustering, enrichment statistical networks, FCROS differential analysis, and random forests. We demonstrate each of these techniques on the Populus trichocarpa gene expression atlas.</div>
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Network Modeling of Complex Data Sets.

Network Modeling of Complex Data Sets.

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Abstract

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