Pattern recognition methods to relate time profiles of gene expression with phenotypic data: a comparative study. - Wikidata - awgldk - TriplyDB

Pattern recognition methods to relate time profiles of gene expression with phenotypic data: a comparative study.

Pattern recognition methods to relate time profiles of gene expression with phenotypic data: a comparative study.

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Dynamics in Transcriptomics: Advancements in RNA-seq Time Course and Downstream Analysis DTNI: a novel toxicogenomics data analysis tool for identifying the molecular mechanisms underlying the adverse effects of toxic compounds.

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Pattern recognition methods to relate time profiles of gene expression with phenotypic data: a comparative study.

http://www.wikidata.org/entity/Q30896775

description

2015 nî lūn-bûn

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2015 թուականի Փետրուարին հրատարակուած գիտական յօդուած

@hyw

2015 թվականի փետրվարին հրատարակված գիտական հոդված

@hy

2015年の論文

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2015年論文

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2015年論文

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2015年論文

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2015年論文

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2015年論文

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2015年论文

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name

Pattern recognition methods to ...... pic data: a comparative study.

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Pattern recognition methods to ...... pic data: a comparative study.

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type

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Pattern recognition methods to ...... pic data: a comparative study.

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Pattern recognition methods to ...... pic data: a comparative study.

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Pattern recognition methods to ...... pic data: a comparative study.

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Pattern recognition methods to ...... pic data: a comparative study.

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Pattern recognition methods to ...... pic data: a comparative study.

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Danyel G J Jennen

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Jacob J Briedé

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Jos C S Kleinjans

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Rachel Cavill

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Theo M de Kok

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P2860

WGCNA: an R package for weighted correlation network analysis

The Hallmarks of Cancer

Hallmarks of Cancer: The Next Generation

Cancer risk assessment, indicators, and guidelines for polycyclic aromatic hydrocarbons in the ambient air

Consensus clustering and functional interpretation of gene-expression data

Pattern recognition in bioinformatics

Analysis of time-resolved gene expression measurements across individuals

limma powers differential expression analyses for RNA-sequencing and microarray studies

Efficient statistical significance approximation for local similarity analysis of high-throughput time series data

Analyzing time series gene expression data.

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2115-2122

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scholarly article

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10.1093/BIOINFORMATICS/BTV108

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13

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31

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Diana M. Hendrickx

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2015-02-19T00:00:00Z

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25701576

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