Reference : BioTextQuest+: a knowledge integration platform for literature mining and concept dis...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/17936
BioTextQuest+: a knowledge integration platform for literature mining and concept discovery
English
Papanikolaou, Nikolas []
Pavlopoulos, Georgios A. []
Pafilis, Evangelos []
Theodosiou, Theodosios []
Schneider, Reinhard mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Satagopam, Venkata P. [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)]
Ouzounis, Christos []
Eliopoulos, Arisitdes []
Promponas, Vasilis []
Iliopoulos, Ioannis []
6-Aug-2014
Bioinformatics
Oxford University Press - Journals Department
Yes (verified by ORBilu)
International
1367-4803
1460-2059
Oxford
United Kingdom
[en] text-mining ; bioinformatics
[en] The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed® and related biological databases. Herein, we describe BioTextQuest+, a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest+ enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest+ addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest+ through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
http://hdl.handle.net/10993/17936
10.1093/bioinformatics/btu524
http://bioinformatics.med.uoc.gr/biotextquest.

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