Literature DB >> 17823133

Medline search engine for finding genetic markers with biological significance.

Weijian Xuan1, Pinglang Wang, Stanley J Watson, Fan Meng.   

Abstract

MOTIVATION: Genome-wide high density SNP association studies are expected to identify various SNP alleles associated with different complex disorders. Understanding the biological significance of these SNP alleles in the context of existing literature is a major challenge since existing search engines are not designed to search literature for SNPs or other genetic markers. The literature mining of gene and protein functions has received significant attention and effort while similar work on genetic markers and their related diseases is still in its infancy. Our goal is to develop a web-based tool that facilitates the mining of Medline literature related to genetic studies and gene/protein function studies. Our solution consists of four main function modules for (1) identification of different types of genetic markers or genetic variations in Medline records (2) distinguishing positive versus negative linkage or association between genetic markers and diseases (3) integrating marker genomic location data from different databases to enable the retrieval of Medline records related to markers in the same linkage disequilibrium region (4) and a web interface called MarkerInfoFinder to search, display, sort and download Medline citation results. Tests using published data suggest MarkerInfoFinder can significantly increase the efficiency of finding genetic disorders and their underlying molecular mechanisms. The functions we developed will also be used to build a knowledge base for genetic markers and diseases. AVAILABILITY: The MarkerInfoFinder is publicly available at: http://brainarray.mbni.med.umich.edu/brainarray/datamining/MarkerInfoFinder.

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Year:  2007        PMID: 17823133     DOI: 10.1093/bioinformatics/btm375

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  11 in total

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Review 2.  Recent progress in automatically extracting information from the pharmacogenomic literature.

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3.  Category fluency, latent semantic analysis and schizophrenia: a candidate gene approach.

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4.  Teaching computers to read the pharmacogenomics literature ... so you don't have to.

Authors:  Yael Garten; Russ B Altman
Journal:  Pharmacogenomics       Date:  2010-04       Impact factor: 2.533

5.  Computational analysis of deleterious single nucleotide polymorphisms in catechol O-Methyltransferase conferring risk to post-traumatic stress disorder.

Authors:  Kumaraswamy Naidu Chitrala; Prakash Nagarkatti; Mitzi Nagarkatti
Journal:  J Psychiatr Res       Date:  2021-03-31       Impact factor: 4.791

6.  Cross-domain neurobiology data integration and exploration.

Authors:  Weijian Xuan; Manhong Dai; Josh Buckner; Barbara Mirel; Jean Song; Brian Athey; Stanley J Watson; Fan Meng
Journal:  BMC Genomics       Date:  2010-12-01       Impact factor: 3.969

7.  pubmed2ensembl: a resource for mining the biological literature on genes.

Authors:  Joachim Baran; Martin Gerner; Maximilian Haeussler; Goran Nenadic; Casey M Bergman
Journal:  PLoS One       Date:  2011-09-29       Impact factor: 3.240

8.  Mutation extraction tools can be combined for robust recognition of genetic variants in the literature.

Authors:  Antonio Jimeno Yepes; Karin Verspoor
Journal:  F1000Res       Date:  2014-01-21

Review 9.  Linking genes to literature: text mining, information extraction, and retrieval applications for biology.

Authors:  Martin Krallinger; Alfonso Valencia; Lynette Hirschman
Journal:  Genome Biol       Date:  2008-09-01       Impact factor: 13.583

10.  Literature mining of genetic variants for curation: quantifying the importance of supplementary material.

Authors:  Antonio Jimeno Yepes; Karin Verspoor
Journal:  Database (Oxford)       Date:  2014-02-10       Impact factor: 3.451

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