DDMGD


25398897	DDMGD: the database of text-mined associations between genes methylated in diseases from different species. [PMID: 25398897] Bin Raies A, Mansour H, Incitti R, Bajic VB. Abstract Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD's scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. Nucleic Acids Res. 2015:43(Database issue) \| 10 Citations (from Europe PMC, 2025-03-29)

DDMGD: the database of text-mined associations between genes methylated in diseases from different species. [PMID: 25398897]

Bin Raies A, Mansour H, Incitti R, Bajic VB.

Abstract

Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD's scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2015:43(Database issue) | 10 Citations (from Europe PMC, 2025-03-29)

URL:	http://www.cbrc.kaust.edu.sa/ddmgd/
Full name:	Dragon Database for Methylated Genes and Diseases
Description:	DDMGD is a database of text-mined associations between genes methylated in diseases from different species. DDMGD's scope is not limited to a particular group of genes, diseases or species. The associations were extracted from individual sentences from more than 50,000 documents. The accuracy of extracted information is 82% as estimated on 2500 hand-curated sentences.
Year founded:	2015
Last update:	NA
Version:	v1.0
Accessibility:	Accessible
Country/Region:	Saudi Arabia

Data type:	Other
Data object:	Animal Plant
Database category:	Health and medicine Literature Modification
Major species:	Arabidopsis thaliana Bos taurus Caenorhabditis elegans Chaetopterus variopedatus Chlorocebus aethiops Cricetulus griseus Cyprinus carpio Donax trunculus Drosophila melanogaster Echinococcus multilocularis Homo sapiens Mus musculus Oryctolagus cuniculus Ovis aries Polycelis nigra Protopolystoma xenopodis Rattus rattus Schistosoma haematobium Schistosoma japonicum Xenopus laevis
Keywords:	epigenetics gene methylation

University/Institution:	King Abdullah University of Science and Technology
Address:	King Abdullah University of Science and Technology, Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia
City:	Thuwal
Province/State:
Country/Region:	Saudi Arabia
Contact name (PI/Team):	Vladimir B. Bajic
Contact email (PI/Helpdesk):	vladimir.bajic@kaust.edu.sa

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Database Commons a catalog of worldwide biological databases