Modules, networks and systems medicine for understanding disease and aiding diagnosis

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Modules, networks and systems medicine for understanding disease and aiding diagnosis. / Gustafsson, Mika; Nestor, Colm E; Zhang, Huan; Barabási, Albert-László; Baranzini, Sergio; Brunak, Sören; Chung, Kian Fan; Federoff, Howard J; Gavin, Anne-Claude; Meehan, Richard R; Picotti, Paola; Pujana, Miguel Àngel; Rajewsky, Nikolaus; Smith, Kenneth Gc; Sterk, Peter J; Villoslada, Pablo; Benson, Mikael.

In: Genome Medicine, Vol. 6, No. 10, 10.2014, p. 82.

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

Harvard

Gustafsson, M, Nestor, CE, Zhang, H, Barabási, A-L, Baranzini, S, Brunak, S, Chung, KF, Federoff, HJ, Gavin, A-C, Meehan, RR, Picotti, P, Pujana, MÀ, Rajewsky, N, Smith, KG, Sterk, PJ, Villoslada, P & Benson, M 2014, 'Modules, networks and systems medicine for understanding disease and aiding diagnosis', Genome Medicine, vol. 6, no. 10, pp. 82. https://doi.org/10.1186/s13073-014-0082-6

APA

Gustafsson, M., Nestor, C. E., Zhang, H., Barabási, A-L., Baranzini, S., Brunak, S., Chung, K. F., Federoff, H. J., Gavin, A-C., Meehan, R. R., Picotti, P., Pujana, M. À., Rajewsky, N., Smith, K. G., Sterk, P. J., Villoslada, P., & Benson, M. (2014). Modules, networks and systems medicine for understanding disease and aiding diagnosis. Genome Medicine, 6(10), 82. https://doi.org/10.1186/s13073-014-0082-6

Vancouver

Gustafsson M, Nestor CE, Zhang H, Barabási A-L, Baranzini S, Brunak S et al. Modules, networks and systems medicine for understanding disease and aiding diagnosis. Genome Medicine. 2014 Oct;6(10):82. https://doi.org/10.1186/s13073-014-0082-6

Author

Gustafsson, Mika ; Nestor, Colm E ; Zhang, Huan ; Barabási, Albert-László ; Baranzini, Sergio ; Brunak, Sören ; Chung, Kian Fan ; Federoff, Howard J ; Gavin, Anne-Claude ; Meehan, Richard R ; Picotti, Paola ; Pujana, Miguel Àngel ; Rajewsky, Nikolaus ; Smith, Kenneth Gc ; Sterk, Peter J ; Villoslada, Pablo ; Benson, Mikael. / Modules, networks and systems medicine for understanding disease and aiding diagnosis. In: Genome Medicine. 2014 ; Vol. 6, No. 10. pp. 82.

Bibtex

@article{064dd673a3844358a2d503abb9e857f5,
title = "Modules, networks and systems medicine for understanding disease and aiding diagnosis",
abstract = "Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.",
author = "Mika Gustafsson and Nestor, {Colm E} and Huan Zhang and Albert-L{\'a}szl{\'o} Barab{\'a}si and Sergio Baranzini and S{\"o}ren Brunak and Chung, {Kian Fan} and Federoff, {Howard J} and Anne-Claude Gavin and Meehan, {Richard R} and Paola Picotti and Pujana, {Miguel {\`A}ngel} and Nikolaus Rajewsky and Smith, {Kenneth Gc} and Sterk, {Peter J} and Pablo Villoslada and Mikael Benson",
year = "2014",
month = oct,
doi = "10.1186/s13073-014-0082-6",
language = "English",
volume = "6",
pages = "82",
journal = "Genome Medicine",
issn = "1756-994X",
publisher = "BioMed Central Ltd.",
number = "10",

}

RIS

TY - JOUR

T1 - Modules, networks and systems medicine for understanding disease and aiding diagnosis

AU - Gustafsson, Mika

AU - Nestor, Colm E

AU - Zhang, Huan

AU - Barabási, Albert-László

AU - Baranzini, Sergio

AU - Brunak, Sören

AU - Chung, Kian Fan

AU - Federoff, Howard J

AU - Gavin, Anne-Claude

AU - Meehan, Richard R

AU - Picotti, Paola

AU - Pujana, Miguel Àngel

AU - Rajewsky, Nikolaus

AU - Smith, Kenneth Gc

AU - Sterk, Peter J

AU - Villoslada, Pablo

AU - Benson, Mikael

PY - 2014/10

Y1 - 2014/10

N2 - Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.

AB - Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.

U2 - 10.1186/s13073-014-0082-6

DO - 10.1186/s13073-014-0082-6

M3 - Journal article

C2 - 25473422

VL - 6

SP - 82

JO - Genome Medicine

JF - Genome Medicine

SN - 1756-994X

IS - 10

ER -

ID: 128737515