Literature mining for the biologist: from information retrieval to biological discovery

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

Standard

Literature mining for the biologist : from information retrieval to biological discovery. / Jensen, Lars Juhl; Saric, Jasmin; Bork, Peer.

In: Nature Reviews. Genetics, Vol. 7, No. 2, 2006, p. 119-29.

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

Harvard

Jensen, LJ, Saric, J & Bork, P 2006, 'Literature mining for the biologist: from information retrieval to biological discovery', Nature Reviews. Genetics, vol. 7, no. 2, pp. 119-29. https://doi.org/10.1038/nrg1768

APA

Jensen, L. J., Saric, J., & Bork, P. (2006). Literature mining for the biologist: from information retrieval to biological discovery. Nature Reviews. Genetics, 7(2), 119-29. https://doi.org/10.1038/nrg1768

Vancouver

Jensen LJ, Saric J, Bork P. Literature mining for the biologist: from information retrieval to biological discovery. Nature Reviews. Genetics. 2006;7(2):119-29. https://doi.org/10.1038/nrg1768

Author

Jensen, Lars Juhl ; Saric, Jasmin ; Bork, Peer. / Literature mining for the biologist : from information retrieval to biological discovery. In: Nature Reviews. Genetics. 2006 ; Vol. 7, No. 2. pp. 119-29.

Bibtex

@article{02492d76c02a4e53a3e6887d4d7d9bd7,
title = "Literature mining for the biologist: from information retrieval to biological discovery",
abstract = "For the average biologist, hands-on literature mining currently means a keyword search in PubMed. However, methods for extracting biomedical facts from the scientific literature have improved considerably, and the associated tools will probably soon be used in many laboratories to automatically annotate and analyse the growing number of system-wide experimental data sets. Owing to the increasing body of text and the open-access policies of many journals, literature mining is also becoming useful for both hypothesis generation and biological discovery. However, the latter will require the integration of literature and high-throughput data, which should encourage close collaborations between biologists and computational linguists.",
author = "Jensen, {Lars Juhl} and Jasmin Saric and Peer Bork",
year = "2006",
doi = "10.1038/nrg1768",
language = "English",
volume = "7",
pages = "119--29",
journal = "Nature Reviews. Genetics",
issn = "1471-0056",
publisher = "nature publishing group",
number = "2",

}

RIS

TY - JOUR

T1 - Literature mining for the biologist

T2 - from information retrieval to biological discovery

AU - Jensen, Lars Juhl

AU - Saric, Jasmin

AU - Bork, Peer

PY - 2006

Y1 - 2006

N2 - For the average biologist, hands-on literature mining currently means a keyword search in PubMed. However, methods for extracting biomedical facts from the scientific literature have improved considerably, and the associated tools will probably soon be used in many laboratories to automatically annotate and analyse the growing number of system-wide experimental data sets. Owing to the increasing body of text and the open-access policies of many journals, literature mining is also becoming useful for both hypothesis generation and biological discovery. However, the latter will require the integration of literature and high-throughput data, which should encourage close collaborations between biologists and computational linguists.

AB - For the average biologist, hands-on literature mining currently means a keyword search in PubMed. However, methods for extracting biomedical facts from the scientific literature have improved considerably, and the associated tools will probably soon be used in many laboratories to automatically annotate and analyse the growing number of system-wide experimental data sets. Owing to the increasing body of text and the open-access policies of many journals, literature mining is also becoming useful for both hypothesis generation and biological discovery. However, the latter will require the integration of literature and high-throughput data, which should encourage close collaborations between biologists and computational linguists.

U2 - 10.1038/nrg1768

DO - 10.1038/nrg1768

M3 - Journal article

C2 - 16418747

VL - 7

SP - 119

EP - 129

JO - Nature Reviews. Genetics

JF - Nature Reviews. Genetics

SN - 1471-0056

IS - 2

ER -

ID: 40740501