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

Research output: Contribution to journal › Letter › Research › peer-review

Standard

A scored human protein-protein interaction network to catalyze genomic interpretation. / Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B; Horn, Heiko; Mercer, Johnathan; Slodkowicz, Greg; Workman, Christopher T; Rigina, Olga; Rapacki, Kristoffer; Stærfeldt, Hans H; Brunak, Søren; Jensen, Thomas S; Hansen, Kasper Lage.

In: Nature Methods, Vol. 14, No. 1, 01.2017, p. 61–64.

Research output: Contribution to journal › Letter › Research › peer-review

Harvard

Li, T, Wernersson, R, Hansen, RB, Horn, H, Mercer, J, Slodkowicz, G, Workman, CT, Rigina, O, Rapacki, K, Stærfeldt, HH, Brunak, S, Jensen, TS & Hansen, KL 2017, 'A scored human protein-protein interaction network to catalyze genomic interpretation', Nature Methods, vol. 14, no. 1, pp. 61–64. https://doi.org/10.1038/nmeth.4083

APA

Li, T., Wernersson, R., Hansen, R. B., Horn, H., Mercer, J., Slodkowicz, G., Workman, C. T., Rigina, O., Rapacki, K., Stærfeldt, H. H., Brunak, S., Jensen, T. S., & Hansen, K. L. (2017). A scored human protein-protein interaction network to catalyze genomic interpretation. Nature Methods, 14(1), 61–64. https://doi.org/10.1038/nmeth.4083

Vancouver

Li T, Wernersson R, Hansen RB, Horn H, Mercer J, Slodkowicz G et al. A scored human protein-protein interaction network to catalyze genomic interpretation. Nature Methods. 2017 Jan;14(1):61–64. https://doi.org/10.1038/nmeth.4083

Author

Li, Taibo ; Wernersson, Rasmus ; Hansen, Rasmus B ; Horn, Heiko ; Mercer, Johnathan ; Slodkowicz, Greg ; Workman, Christopher T ; Rigina, Olga ; Rapacki, Kristoffer ; Stærfeldt, Hans H ; Brunak, Søren ; Jensen, Thomas S ; Hansen, Kasper Lage. / A scored human protein-protein interaction network to catalyze genomic interpretation. In: Nature Methods. 2017 ; Vol. 14, No. 1. pp. 61–64.

Bibtex

@article{29f75dc33a424ee7802c1cf9a2aa9fc7,
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 Greg Slodkowicz and Workman, {Christopher T} and Olga Rigina and Kristoffer Rapacki and St{\ae}rfeldt, {Hans H} and S{\o}ren Brunak and Jensen, {Thomas S} and Hansen, {Kasper Lage}",
year = "2017",
month = jan,
doi = "10.1038/nmeth.4083",
language = "English",
volume = "14",
pages = "61–64",
journal = "Nature Methods",
issn = "1548-7091",
publisher = "nature publishing group",
number = "1",

}

RIS

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, Greg

AU - Workman, Christopher T

AU - Rigina, Olga

AU - Rapacki, Kristoffer

AU - Stærfeldt, Hans H

AU - Brunak, Søren

AU - Jensen, Thomas S

AU - Hansen, Kasper Lage

PY - 2017/1

Y1 - 2017/1

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 - Letter

C2 - 27892958

VL - 14

SP - 61

EP - 64

JO - Nature Methods

JF - Nature Methods

SN - 1548-7091

IS - 1

ER -

ID: 169733207