Sequential Pattern Mining for Discovering Gene Interactions and their Contextual Information from Biomedical Texts

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00229981" target="_blank" >RIV/68407700:21230/15:00229981 - isvavai.cz</a>

Result on the web

<a href="http://www.biomedcentral.com/content/pdf/s13326-015-0023-3.pdf" target="_blank" >http://www.biomedcentral.com/content/pdf/s13326-015-0023-3.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s13326-015-0023-3" target="_blank" >10.1186/s13326-015-0023-3</a>

Result language

angličtina

Original language name

Sequential Pattern Mining for Discovering Gene Interactions and their Contextual Information from Biomedical Texts

Original language description

BACKGROUND: Discovering gene interactions and their characterizations from biological text collections is a crucial issue in bioinformatics. Indeed, text collections are large and it is very difficult for biologists to fully take benefit from this amountof knowledge. Natural Language Processing (NLP) methods have been applied to extract background knowledge from biomedical texts. Some of existing NLP approaches are based on handcrafted rules and thus are time consuming and often devoted to a specific corpus. Machine learning based NLP methods, give good results but generate outcomes that are not really understandable by a user. RESULTS: We take advantage of an hybridization of data mining and natural language processing to propose an original symbolicmethod to automatically produce patterns conveying gene interactions and their characterizations. Therefore, our method not only allows gene interactions but also semantics information on the extracted interactions (e.g., modalities, bio

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JC - Computer hardware and software

OECD FORD branch

—

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Biomedical Semantics

ISSN

2041-1480

e-ISSN

—

Volume of the periodical

6:27

Issue of the periodical within the volume

6

Country of publishing house

GB - UNITED KINGDOM

Number of pages

12

Pages from-to

1-12

UT code for WoS article

000354922800001

EID of the result in the Scopus database

2-s2.0-84938814624