Predicting biological networks from genomic data

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Predicting biological networks from genomic data. / Harrington, Eoghan D; Jensen, Lars J; Bork, Peer.

In: F E B S Letters, Vol. 582, No. 8, 2008, p. 1251-8.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Harrington, ED, Jensen, LJ & Bork, P 2008, 'Predicting biological networks from genomic data', F E B S Letters, vol. 582, no. 8, pp. 1251-8. https://doi.org/10.1016/j.febslet.2008.02.033

APA

Harrington, E. D., Jensen, L. J., & Bork, P. (2008). Predicting biological networks from genomic data. F E B S Letters, 582(8), 1251-8. https://doi.org/10.1016/j.febslet.2008.02.033

Vancouver

Harrington ED, Jensen LJ, Bork P. Predicting biological networks from genomic data. F E B S Letters. 2008;582(8):1251-8. https://doi.org/10.1016/j.febslet.2008.02.033

Author

Harrington, Eoghan D ; Jensen, Lars J ; Bork, Peer. / Predicting biological networks from genomic data. In: F E B S Letters. 2008 ; Vol. 582, No. 8. pp. 1251-8.

Bibtex

@article{12679b03923e4ea4b81d98cdf0253951,
title = "Predicting biological networks from genomic data",
abstract = "Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.",
keywords = "Computational Biology, Genomics, Phylogeny",
author = "Harrington, {Eoghan D} and Jensen, {Lars J} and Peer Bork",
year = "2008",
doi = "10.1016/j.febslet.2008.02.033",
language = "English",
volume = "582",
pages = "1251--8",
journal = "F E B S Letters",
issn = "0014-5793",
publisher = "JohnWiley & Sons Ltd",
number = "8",

}

RIS

TY - JOUR

T1 - Predicting biological networks from genomic data

AU - Harrington, Eoghan D

AU - Jensen, Lars J

AU - Bork, Peer

PY - 2008

Y1 - 2008

N2 - Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.

AB - Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.

KW - Computational Biology

KW - Genomics

KW - Phylogeny

U2 - 10.1016/j.febslet.2008.02.033

DO - 10.1016/j.febslet.2008.02.033

M3 - Journal article

C2 - 18294967

VL - 582

SP - 1251

EP - 1258

JO - F E B S Letters

JF - F E B S Letters

SN - 0014-5793

IS - 8

ER -

ID: 40749019