Title

ThalInd, a beta-thalassemia and hemoglobinopathies database for India: Defining a model country-specific and disease-centric bioinformatics resource

Document Type

Journal Article

Publisher

Elsevier

Faculty

Faculty of Computing, Health and Science

School

School of Medical Sciences

RAS ID

12357

Comments

This article was originally published as: Sinha, S., Black, M., Agarwal, S., Das, R., Bittles, A. H., & Bellgard, M. (2011). ThalInd, a beta-thalassemia and hemoglobinopathies database for India: Defining a model country-specific and disease-centric bioinformatics resource. Human Mutation, 32(8), 887-893. Original article available here

Abstract

Web-based informatics resources for genetic disorders have evolved from genome-wide databases like OMIM and HGMD to Locus Specific databases (LSDBs) and National and Ethnic Mutation Databases (NEMDBs). However, with the increasing amenability of genetic disorders to diagnosis and better management, many previously underreported conditions are emerging as disorders of public health significance. In turn, the greater emphasis on noncommunicable disorders has generated a demand for comprehensive and relevant disease-based information from end-users, including clinicians, patients, genetic epidemiologists, health administrators and policymakers. To accommodate these demands, country-specific and disease-centric resources are required to complement the existing LSDBs and NEMDBs. Currently available preconfigured Web-based software applications can be customized for this purpose. The present article describes the formulation and construction of a Web-based informatics resource for β-thalassemia and other hemoglobinopathies, initially for use in India, a multiethnic, multireligious country with a population approaching 1,200 million. The resource ThalInd (http://ccg.murdoch.edu.au/thalind) has been created using the LOVD system, an open source platform-independent database system. The system has been customized to incorporate and accommodate data pertinent to molecular genetics, population genetics, genotype–phenotype correlations, disease burden, and infrastructural assessment. Importantly, the resource also has been aligned with the administrative health system and demographic resources of the country.

 

Link to publisher version (DOI)

10.1002/humu.21510