A scored human protein-protein interaction network to catalyze genomic interpretation

Taibo Li; Rasmus Wernersson; Rasmus B Hansen; Heiko Horn; Johnathan Mercer; Grzegorz Slodkowicz; Christopher T. Workman; Olga Rigina; Kristoffer Rapacki; Hans Henrik Stærfeldt; Søren Brunak; Thomas S. Jensen; Kasper Lage

doi:10.1038/nmeth.4083

A scored human protein-protein interaction network to catalyze genomic interpretation

Taibo Li, Rasmus Wernersson, Rasmus B Hansen, Heiko Horn, Johnathan Mercer, Grzegorz Slodkowicz, Christopher T. Workman, Olga Rigina, Kristoffer Rapacki, Hans Henrik Stærfeldt, Søren Brunak, Thomas S. Jensen, Kasper Lage

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

Original language	English
Journal	Nature Methods
Volume	14
Pages (from-to)	61–64
Number of pages	6
ISSN	1548-7091
DOIs	https://doi.org/10.1038/nmeth.4083
Publication status	Published - 2017

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title = "A scored human protein-protein interaction network to catalyze genomic interpretation",

abstract = "Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.",

author = "Taibo Li and Rasmus Wernersson and Hansen, {Rasmus B} and Heiko Horn and Johnathan Mercer and Grzegorz Slodkowicz and Workman, {Christopher T.} and Olga Rigina and Kristoffer Rapacki and St{\ae}rfeldt, {Hans Henrik} and S{\o}ren Brunak and Jensen, {Thomas S.} and Kasper Lage",

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journal = "Nature Methods",

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TY - JOUR

T1 - A scored human protein-protein interaction network to catalyze genomic interpretation

AU - Li, Taibo

AU - Wernersson, Rasmus

AU - Hansen, Rasmus B

AU - Horn, Heiko

AU - Mercer, Johnathan

AU - Slodkowicz, Grzegorz

AU - Workman, Christopher T.

AU - Rigina, Olga

AU - Rapacki, Kristoffer

AU - Stærfeldt, Hans Henrik

AU - Brunak, Søren

AU - Jensen, Thomas S.

AU - Lage, Kasper

PY - 2017

Y1 - 2017

N2 - Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

AB - Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold more interactions (>500,000) and better functional biological relevance than comparable resources. We illustrate that InWeb_InBioMap enables functional interpretation of >4,700 cancer genomes and genes involved in autism.

U2 - 10.1038/nmeth.4083

DO - 10.1038/nmeth.4083

M3 - Journal article

C2 - 27892958

VL - 14

SP - 61

EP - 64

JO - Nature Methods

JF - Nature Methods

SN - 1548-7091

ER -

A scored human protein-protein interaction network to catalyze genomic interpretation

Abstract

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