Literature DB >> 14663965

Improving literature based discovery support by genetic knowledge integration.

Dimitar Hristovski1, Borut Peterlin, Joyce A Mitchell, Susanne M Humphrey.   

Abstract

We present an interactive literature based biomedical discovery support system (BITOLA). The goal of the system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database Medline. To make the system more suitable for disease candidate gene discovery and to decrease the number of candidate relations, we integrate background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as LocusLink, HUGO and OMIM. The BITOLA system can be also used as an alternative way of searching the Medline database. The system is available at http://www.mf.uni-lj.si/bitola/.

Mesh:

Year:  2003        PMID: 14663965

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  13 in total

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5.  Can the vector space model be used to identify biological entity activities?

Authors:  Wesley D Maciel; Alessandra C Faria-Campos; Marcos A Gonçalves; Sérgio V A Campos
Journal:  BMC Genomics       Date:  2011-12-22       Impact factor: 3.969

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7.  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

8.  DEOP: a database on osmoprotectants and associated pathways.

Authors:  Salim Bougouffa; Aleksandar Radovanovic; Magbubah Essack; Vladimir B Bajic
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9.  Context-driven automatic subgraph creation for literature-based discovery.

Authors:  Delroy Cameron; Ramakanth Kavuluru; Thomas C Rindflesch; Amit P Sheth; Krishnaprasad Thirunarayan; Olivier Bodenreider
Journal:  J Biomed Inform       Date:  2015-02-07       Impact factor: 6.317

10.  Conceptual biology, hypothesis discovery, and text mining: Swanson's legacy.

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Journal:  Biomed Digit Libr       Date:  2006-04-03
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