BioTextQuest + : a knowledge integration platform for literature mining and concept discovery

Autor: Papanikolaou, Nikolas, Pavlopoulos, Georgios A., Pafilis, Evangelos, Theodosiou, Theodosios G., Schneider, R., Satagopam, V. P., Ouzounis, Christos A., Eliopoulos, Aristides G., Promponas, Vasilis J., Iliopoulos, Ioannis Crete
Přispěvatelé: Promponas, Vasilis J. [0000-0003-3352-4831], Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center]
Rok vydání: 2014
Předmět:
Computer science
Biological database
Biochemistry
biophysics & molecular biology [F05] [Life sciences]
computer.software_genre
01 natural sciences
Biochemistry
Computational biology
Medical Subject Headings
Knowledge extraction
Knowledge integration
computer program
Cluster Analysis
Data Mining
Software mining
genetics
Disease
Biochimie
biophysique & biologie moléculaire [F05] [Sciences du vivant]
Publications
Medline
Genomics
bioinformatics
writing
Biomedical text mining
Computer Science Applications
Data processing
Computational Mathematics
publication
Computational Theory and Mathematics
Data integration
Statistics and Probability
PubMed
010402 general chemistry
diseases
Text mining
Humans
human
procedures
gene
Molecular Biology
Internet
Information retrieval
010405 organic chemistry
business.industry
text-mining
Proteins
data mining
Document clustering
Authorship
0104 chemical sciences
ComputingMethodologies_PATTERNRECOGNITION
Genes
Web mining
protein
business
computer
Software
cluster analysis
Zdroj: Bioinformatics
Bioinformatics. Oxford, United Kingdom: Oxford University Press-Journals Department (2014).
ISSN: 1460-2059
1367-4803
DOI: 10.1093/bioinformatics/btu524
Popis: Summary: 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. Availability: The service is accessible at http://bioinformatics.med.uoc.gr/biotextquest . Contact: g.pavlopoulos@gmail.com or georgios.pavlopoulos@esat.kuleuven.be Supplementary information: Supplementary data are available at Bioinformatics online.
Databáze: OpenAIRE
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