Introducing the medical bioinformatics in Journal of Translational Medicine
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EDITORIAL
Open Access
Introducing the medical bioinformatics in Journal of Translational Medicine Samir K Brahmachari1,2,3 Abstract The explosion of genome sequencing data along with genotype to phenotype correlation studies has created data deluge in the area of biomedical sciences. The aim of the Medical bioinformatics section is to aid the development and maturation of the field by providing a platform for the translation of these datasets into useful clinical applications. The increase in computing capabilities and availability of different data from advanced technologies will allow researchers to build System Biology models of various diseases in order to efficiently develop new therapeutic interventions and reduce the current prohibitively large costs of drug discovery. The section welcomes studies on the development of Biomedical Informatics for translational medicine and clinical applications, including tools, methodologies and data integration. Launched with the promise of improving insights into human health and disease, the Human Genome Project a decade after its completion has revealed a wealth of information. The advent of next generation sequencing technologies and other high throughput measurements of ‘omics’ data, along with clinical phenotype association studies, have created a data deluge. However, explosive growth in biomedical data generation has not yet translated to proportionate increases in clinical returns. The announcement of the X-prize in genomics for sequencing 100 centenarians within 30 days at less than $1,000 per genome, and with an error rate less than one in a million base pairs, is expected to herald a new era, where whole genome sequencing will become routine clinical practice for diagnosis and prognosis for personalized healthcare [1]. However, this would only be possible if we are able to capture, curate and analyze clinical data with ‘omics’ datasets using novel informatics tools to establish correlations with high level of confidence. This major transformation that hoped to bridge the gap between researchers and clinicians will primarily be driven by transformation of silos of biomedical research to an integrative field of intensive data driven discovery. * Correspondence: [email protected] 1 CSIR-Institute of Genomics and Integrative Biology, Mall Road, New Delhi 110007, India 2 CSIR- Open Source Drug Discovery (OSDD) unit, Anusandhan Bhavan, 2 Rafi Marg, New Delhi 110001, India Full list of author information is available at the end of the article
The new paradigm of scientific discovery arising out of this data exploration is referred to as the “Fourth Paradigm” [2] and combines data capture, theory and computation. This paradigm rests on the power of information technology and advance computing facility to effectively mine semantically linked datasets to derive patterns and predictive models. ‘Medical Bioinformatics’ holds immense promise in this area by equipping researchers with tools and resources to efficiently capture, curate and analyze the ‘big data’, while allowi
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