Abstract
BackgroundSickle cell disease (SCD) is a fatal monogenic disorder with no effective cure and thus high rates of morbidity and sequelae. Efforts toward discovery of disease modifying drugs and curative strategies can be augmented by leveraging the plethora of information contained in available biomedical literature. To facilitate research in this direction we have developed a resource, Dragon Exploration System for Sickle Cell Disease (DESSCD) (http://cbrc.kaust.edu.sa/desscd/) that aims to promote the easy exploration of SCD-related data.DescriptionThe Dragon Exploration System (DES), developed based on text mining and complemented by data mining, processed 419,612 MEDLINE abstracts retrieved from a PubMed query using SCD-related keywords. The processed SCD-related data has been made available via the DESSCD web query interface that enables: a/information retrieval using specified concepts, keywords and phrases, and b/the generation of inferred association networks and hypotheses. The usefulness of the system is demonstrated by: a/reproducing a known scientific fact, the “Sickle_Cell_Anemia–Hydroxyurea” association, and b/generating novel and plausible “Sickle_Cell_Anemia–Hydroxyfasudil” hypothesis. A PCT patent (PCT/US12/55042) has been filed for the latter drug repurposing for SCD treatment.ConclusionWe developed the DESSCD resource dedicated to exploration of text-mined and data-mined information about SCD. No similar SCD-related resource exists. Thus, we anticipate that DESSCD will serve as a valuable tool for physicians and researchers interested in SCD.
Highlights
As a life-threatening monogenic disorder, Sickle cell disease (SCD) is the most common and is common among people with sub-Saharan African, South American, Central American, Saudi Arabian, Indian, Turkish, Greek, and Italian ancestry [1]
We developed the Dragon Exploration System for Sickle Cell Disease (DESSCD) resource dedicated to exploration of text-mined and data-mined information about SCD
The performances of few of these Literature Based Discovery (LBD) tools such as the DAD-system [28], Anni 2.0 [29], and the Dragon Exploration System (DES) resource DESHCV [27] have been evaluated by simulating a confirmed scientific discovery. Another DES resource, DDESC evaluated the performance of DES and reported that the precision and recall for identified concepts from ‘‘Human Genes and Proteins’’ dictionary was lower than the other dictionaries, with precision, recall and F-measure of 81.1%, 96.1% and 87,9%, respectively [20]
Summary
We developed a user-friendly SCD-specific knowledgebase for the comprehensive probing for links between biomedical concepts. We have demonstrated that the system successfully reproduced the known ‘‘Sickle_Cell_Anemia–Hydroxyurea’’ link and generated novel and plausible ‘‘Sickle_Cell_Anemia–Hydroxyfasudil’’ hypothesis. The knowledgebase relies on the extracted textual data
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