TY - JOUR
T1 - MET network in PubMed
T2 - a text-mined network visualization and curation system
AU - Dai, Hong Jie
AU - Su, Chu Hsien
AU - Lai, Po Ting
AU - Huang, Ming Siang
AU - Jonnagaddala, Jitendra
AU - Rose Jue, Toni
AU - Rao, Shruti
AU - Chou, Hui Jou
AU - Milacic, Marija
AU - Singh, Onkar
AU - Syed-Abdul, Shabbir
AU - Hsu, Wen Lian
N1 - Publisher Copyright:
© The Author(s) 2016. Published by Oxford University Press.
PY - 2016
Y1 - 2016
N2 - Metastasis is the dissemination of a cancer/tumor from one organ to another, and it is the most dangerous stage during cancer progression, causing more than 90% of cancer deaths. Improving the understanding of the complicated cellular mechanisms underlying metastasis requires investigations of the signaling pathways. To this end, we developed a METastasis (MET) network visualization and curation tool to assist metastasis researchers retrieve network information of interest while browsing through the large volume of studies in PubMed. MET can recognize relations among genes, cancers, tissues and organs of metastasis mentioned in the literature through text-mining techniques, and then produce a visualization of all mined relations in a metastasis network. To facilitate the curation process, MET is developed as a browser extension that allows curators to review and edit concepts and relations related to metastasis directly in PubMed. PubMed users can also view the metastatic networks integrated from the large collection of research papers directly through MET. For the BioCreative 2015 interactive track (IAT), a curation task was proposed to curate metastatic networks among PubMed abstracts. Six curators participated in the proposed task and a post-IAT task, curating 963 unique metastatic relations from 174 PubMed abstracts using MET.Database URL: http://btm.tmu.edu.tw/metastasisway.
AB - Metastasis is the dissemination of a cancer/tumor from one organ to another, and it is the most dangerous stage during cancer progression, causing more than 90% of cancer deaths. Improving the understanding of the complicated cellular mechanisms underlying metastasis requires investigations of the signaling pathways. To this end, we developed a METastasis (MET) network visualization and curation tool to assist metastasis researchers retrieve network information of interest while browsing through the large volume of studies in PubMed. MET can recognize relations among genes, cancers, tissues and organs of metastasis mentioned in the literature through text-mining techniques, and then produce a visualization of all mined relations in a metastasis network. To facilitate the curation process, MET is developed as a browser extension that allows curators to review and edit concepts and relations related to metastasis directly in PubMed. PubMed users can also view the metastatic networks integrated from the large collection of research papers directly through MET. For the BioCreative 2015 interactive track (IAT), a curation task was proposed to curate metastatic networks among PubMed abstracts. Six curators participated in the proposed task and a post-IAT task, curating 963 unique metastatic relations from 174 PubMed abstracts using MET.Database URL: http://btm.tmu.edu.tw/metastasisway.
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U2 - 10.1093/database/baw090
DO - 10.1093/database/baw090
M3 - Article
C2 - 27242035
AN - SCOPUS:85009854787
SN - 1758-0463
VL - 2016
JO - Database : the journal of biological databases and curation
JF - Database : the journal of biological databases and curation
ER -
