Literature DB >> 20351860

Semantic relations for interpreting DNA microarray data.

Dimitar Hristovski1, Andrej Kastrin, Borut Peterlin, Thomas C Rindflesch.   

Abstract

The results from microarray experiments, in the form of lists of over- and under-expressed genes, have great potential to support progress in biomedical research. However, results are not easy to interpret. Information about the function of the genes and their relation to other genes is needed, and this information is usually present in vast amounts of biomedical literature. Considerable effort is required to find, read and extract relevant information from the literature. A potential solution is to use computerized text analysis methods to extract relevant information. Our proposal enhances current methods in this regard and uses semantic relations extracted from biomedical text with the SemRep information extraction system. We describe an application that integrates microarray results with semantic relations and discuss its benefits in supporting enhanced access to the relevant literature for interpretation of results.

Mesh:

Year:  2009        PMID: 20351860      PMCID: PMC2815475     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  20 in total

1.  Genes, themes and microarrays: using information retrieval for large-scale gene analysis.

Authors:  H Shatkay; S Edwards; W J Wilbur; M Boguski
Journal:  Proc Int Conf Intell Syst Mol Biol       Date:  2000

2.  Text mining biomedical literature for discovering gene-to-gene relationships: a comparative study of algorithms.

Authors:  Ying Liu; Shamkant B Navathe; Jorge Civera; Venu Dasigi; Ashwin Ram; Brian J Ciliax; Ray Dingledine
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2005 Jan-Mar       Impact factor: 3.710

3.  Extracting semantic predications from Medline citations for pharmacogenomics.

Authors:  Caroline B Ahlers; Marcelo Fiszman; Dina Demner-Fushman; François-Michel Lang; Thomas C Rindflesch
Journal:  Pac Symp Biocomput       Date:  2007

4.  Clustering microarray-derived gene lists through implicit literature relationships.

Authors:  Mark F Burkart; Jonathan D Wren; Jason I Herschkowitz; Charles M Perou; Harold R Garner
Journal:  Bioinformatics       Date:  2007-05-30       Impact factor: 6.937

Review 5.  Microarray data analysis and mining approaches.

Authors:  Francesca Cordero; Marco Botta; Raffaele A Calogero
Journal:  Brief Funct Genomic Proteomic       Date:  2008-01-22

6.  Automatic summarization of mouse gene information by clustering and sentence extraction from MEDLINE abstracts.

Authors:  Jianji Yang; Aaron M Cohen; William Hersh
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

Review 7.  Are Parkinson disease patients protected from some but not all cancers?

Authors:  Rivka Inzelberg; Joseph Jankovic
Journal:  Neurology       Date:  2007-08-15       Impact factor: 9.910

8.  Argument-predicate distance as a filter for enhancing precision in extracting predications on the genetic etiology of disease.

Authors:  Marco Masseroli; Halil Kilicoglu; François-Michel Lang; Thomas C Rindflesch
Journal:  BMC Bioinformatics       Date:  2006-06-08       Impact factor: 3.169

9.  NCBI GEO: mining tens of millions of expression profiles--database and tools update.

Authors:  Tanya Barrett; Dennis B Troup; Stephen E Wilhite; Pierre Ledoux; Dmitry Rudnev; Carlos Evangelista; Irene F Kim; Alexandra Soboleva; Maxim Tomashevsky; Ron Edgar
Journal:  Nucleic Acids Res       Date:  2006-11-11       Impact factor: 16.971

10.  Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease.

Authors:  Rob Jelier; Peter A C 't Hoen; Ellen Sterrenburg; Johan T den Dunnen; Gert-Jan B van Ommen; Jan A Kors; Barend Mons
Journal:  BMC Bioinformatics       Date:  2008-06-24       Impact factor: 3.169

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  2 in total

1.  Networks of neuroinjury semantic predications to identify biomarkers for mild traumatic brain injury.

Authors:  Michael J Cairelli; Marcelo Fiszman; Han Zhang; Thomas C Rindflesch
Journal:  J Biomed Semantics       Date:  2015-05-18

2.  Integration of data from omic studies with the literature-based discovery towards identification of novel treatments for neovascularization in diabetic retinopathy.

Authors:  Ales Maver; Dimitar Hristovski; Thomas C Rindflesch; Borut Peterlin
Journal:  Biomed Res Int       Date:  2013-11-24       Impact factor: 3.411

  2 in total

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