Literature DB >> 22580177

Relation mining experiments in the pharmacogenomics domain.

Fabio Rinaldi1, Gerold Schneider, Simon Clematide.   

Abstract

The mutual interactions among genes, diseases, and drugs are at the heart of biomedical research, and are especially important for the pharmacological industry. The recent trend towards personalized medicine makes it increasingly relevant to be able to tailor drugs to specific genetic makeups. The pharmacogenetics and pharmacogenomics knowledge base (PharmGKB) aims at capturing relevant information about such interactions from several sources, including curation of the biomedical literature. Advanced text mining tools which can support the process of manual curation are increasingly necessary in order to cope with the deluge of new published results. However, effective evaluation of those tools requires the availability of manually curated data as gold standard. In this paper we discuss how the existing PharmGKB database can be used for such an evaluation task in a way similar to the usage of gold standard data derived from protein-protein interaction databases in one of the recent BioCreative shared tasks. Additionally, we present our own considerations and results on the feasibility and difficulty of such a task.
Copyright © 2012 Elsevier Inc. All rights reserved.

Mesh:

Year:  2012        PMID: 22580177     DOI: 10.1016/j.jbi.2012.04.014

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  8 in total

1.  Domain adaption of parsing for operative notes.

Authors:  Yan Wang; Serguei Pakhomov; James O Ryan; Genevieve B Melton
Journal:  J Biomed Inform       Date:  2015-02-07       Impact factor: 6.317

2.  Using ODIN for a PharmGKB revalidation experiment.

Authors:  Fabio Rinaldi; Simon Clematide; Yael Garten; Michelle Whirl-Carrillo; Li Gong; Joan M Hebert; Katrin Sangkuhl; Caroline F Thorn; Teri E Klein; Russ B Altman
Journal:  Database (Oxford)       Date:  2012-04-23       Impact factor: 3.451

3.  OntoGene web services for biomedical text mining.

Authors:  Fabio Rinaldi; Simon Clematide; Hernani Marques; Tilia Ellendorff; Martin Romacker; Raul Rodriguez-Esteban
Journal:  BMC Bioinformatics       Date:  2014-11-27       Impact factor: 3.169

4.  eGARD: Extracting associations between genomic anomalies and drug responses from text.

Authors:  A S M Ashique Mahmood; Shruti Rao; Peter McGarvey; Cathy Wu; Subha Madhavan; K Vijay-Shanker
Journal:  PLoS One       Date:  2017-12-20       Impact factor: 3.240

5.  Strategies towards digital and semi-automated curation in RegulonDB.

Authors:  Fabio Rinaldi; Oscar Lithgow; Socorro Gama-Castro; Hilda Solano; Alejandra Lopez; Luis José Muñiz Rascado; Cecilia Ishida-Gutiérrez; Carlos-Francisco Méndez-Cruz; Julio Collado-Vides
Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

6.  A machine-compiled database of genome-wide association studies.

Authors:  Volodymyr Kuleshov; Jialin Ding; Christopher Vo; Braden Hancock; Alexander Ratner; Yang Li; Christopher Ré; Serafim Batzoglou; Michael Snyder
Journal:  Nat Commun       Date:  2019-07-26       Impact factor: 14.919

7.  Using the OntoGene pipeline for the triage task of BioCreative 2012.

Authors:  Fabio Rinaldi; Simon Clematide; Simon Hafner; Gerold Schneider; Gintare Grigonyte; Martin Romacker; Therese Vachon
Journal:  Database (Oxford)       Date:  2013-02-09       Impact factor: 3.451

8.  PGxCorpus, a manually annotated corpus for pharmacogenomics.

Authors:  Joël Legrand; Romain Gogdemir; Cédric Bousquet; Kevin Dalleau; Marie-Dominique Devignes; William Digan; Chia-Ju Lee; Ndeye-Coumba Ndiaye; Nadine Petitpain; Patrice Ringot; Malika Smaïl-Tabbone; Yannick Toussaint; Adrien Coulet
Journal:  Sci Data       Date:  2020-01-02       Impact factor: 6.444

  8 in total

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