TY - JOUR
T1 - Dragon exploratory system on Hepatitis C Virus (DESHCV)
AU - Kwofie, Samuel K.
AU - Radovanovic, Aleksandar
AU - Sundararajan, Vijayaraghava Seshadri
AU - Maqungo, Monique
AU - Christoffels, Alan G.
AU - Bajic, Vladimir B.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was partly supported by grants from the National Research Foundation (South Africa), National Bioinformatics Network (to S.K.K.), and DST/NRF Research Chair (to A.C.). We are also grateful to A.R. and V.B.B. for making available the DES resource.
PY - 2011/6
Y1 - 2011/6
N2 - Even though Hepatitis C Virus (HCV) cDNA was characterized about 20 years ago, there is insufficient understanding of the molecular etiology underlying HCV infections. Current global rates of infection and its increasingly chronic character are causes of concern for health policy experts. Vast amount of data accumulated from biochemical, genomic, proteomic, and other biological analyses allows for novel insights into the HCV viral structure, life cycle and functions of its proteins. Biomedical text-mining is a useful approach for analyzing the increasing corpus of published scientific literature on HCV. We report here the first comprehensive HCV customized biomedical text-mining based online web resource, dragon exploratory system on Hepatitis C Virus (DESHCV), a biomedical text-mining and relationship exploring knowledgebase was developed by exploring literature on HCV. The pre-compiled dictionaries existing in the dragon exploratory system (DES) were enriched with biomedical concepts pertaining to HCV proteins, their name variants and symbols to make it suitable for targeted information exploration and knowledge extraction as focused on HCV. A list of 32,895 abstracts retrieved via PubMed database using specific keywords searches related to HCV were processed based on concept recognition of terms from several dictionaries. The web query interface enables retrieval of information using specified concepts, keywords and phrases, generating text-derived association networks and hypotheses, which could be tested to identify potentially novel relationship between different concepts. Such an approach could also augment efforts in the search for diagnostic or even therapeutic targets. DESHCV thus represents online literature-based discovery resource freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/DESHCV/ and its mirror site http://cbrc.kaust.edu.sa/deshcv/. © 2010 Elsevier B.V.
AB - Even though Hepatitis C Virus (HCV) cDNA was characterized about 20 years ago, there is insufficient understanding of the molecular etiology underlying HCV infections. Current global rates of infection and its increasingly chronic character are causes of concern for health policy experts. Vast amount of data accumulated from biochemical, genomic, proteomic, and other biological analyses allows for novel insights into the HCV viral structure, life cycle and functions of its proteins. Biomedical text-mining is a useful approach for analyzing the increasing corpus of published scientific literature on HCV. We report here the first comprehensive HCV customized biomedical text-mining based online web resource, dragon exploratory system on Hepatitis C Virus (DESHCV), a biomedical text-mining and relationship exploring knowledgebase was developed by exploring literature on HCV. The pre-compiled dictionaries existing in the dragon exploratory system (DES) were enriched with biomedical concepts pertaining to HCV proteins, their name variants and symbols to make it suitable for targeted information exploration and knowledge extraction as focused on HCV. A list of 32,895 abstracts retrieved via PubMed database using specific keywords searches related to HCV were processed based on concept recognition of terms from several dictionaries. The web query interface enables retrieval of information using specified concepts, keywords and phrases, generating text-derived association networks and hypotheses, which could be tested to identify potentially novel relationship between different concepts. Such an approach could also augment efforts in the search for diagnostic or even therapeutic targets. DESHCV thus represents online literature-based discovery resource freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/DESHCV/ and its mirror site http://cbrc.kaust.edu.sa/deshcv/. © 2010 Elsevier B.V.
UR - http://hdl.handle.net/10754/561787
UR - https://linkinghub.elsevier.com/retrieve/pii/S1567134810003448
UR - http://www.scopus.com/inward/record.url?scp=79956324084&partnerID=8YFLogxK
U2 - 10.1016/j.meegid.2010.12.006
DO - 10.1016/j.meegid.2010.12.006
M3 - Article
C2 - 21194573
SN - 1567-1348
VL - 11
SP - 734
EP - 739
JO - Infection, Genetics and Evolution
JF - Infection, Genetics and Evolution
IS - 4
ER -
