From gene names to actual genes

Ioannis Korkontzelos; Andreas Vlachos; Ian Lewin

From gene names to actual genes

Ioannis Korkontzelos, Andreas Vlachos, Ian Lewin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents an approach of determining automatically whether a noun phrase containing one or more gene names refers to an actual gene or not. The system developed is based on syntactic parsing combined with SVMs and uses training data automatically created by a simple rule-based tagger and it achieves 78.63\%. Such an approach would be useful to other fields which exhibit similar ambiguity in the way names are used to refer to entities.

Original language	English
Title of host publication	The Annual Meeting of ISMB BioLINK Special Interest Group on Text Data Mining
Publication status	Published - 2007

Keywords

bio\_ner

Cite this

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title = "From gene names to actual genes",

abstract = "This paper presents an approach of determining automatically whether a noun phrase containing one or more gene names refers to an actual gene or not. The system developed is based on syntactic parsing combined with SVMs and uses training data automatically created by a simple rule-based tagger and it achieves 78.63\%. Such an approach would be useful to other fields which exhibit similar ambiguity in the way names are used to refer to entities.",

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author = "Ioannis Korkontzelos and Andreas Vlachos and Ian Lewin",

year = "2007",

language = "English",

booktitle = "The Annual Meeting of ISMB BioLINK Special Interest Group on Text Data Mining",

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T1 - From gene names to actual genes

AU - Korkontzelos, Ioannis

AU - Vlachos, Andreas

AU - Lewin, Ian

PY - 2007

Y1 - 2007

N2 - This paper presents an approach of determining automatically whether a noun phrase containing one or more gene names refers to an actual gene or not. The system developed is based on syntactic parsing combined with SVMs and uses training data automatically created by a simple rule-based tagger and it achieves 78.63\%. Such an approach would be useful to other fields which exhibit similar ambiguity in the way names are used to refer to entities.

AB - This paper presents an approach of determining automatically whether a noun phrase containing one or more gene names refers to an actual gene or not. The system developed is based on syntactic parsing combined with SVMs and uses training data automatically created by a simple rule-based tagger and it achieves 78.63\%. Such an approach would be useful to other fields which exhibit similar ambiguity in the way names are used to refer to entities.

KW - bio\_ner

M3 - Conference contribution

BT - The Annual Meeting of ISMB BioLINK Special Interest Group on Text Data Mining

ER -

From gene names to actual genes

Abstract

Keywords

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Cite this