NGS and data management
Since the beginning of the Human Genome Project, data management has been perceived as a key challenge for current molecular biology research. Before the finish of the nineties, advances had been set up that adequately bolstered most continuous activities, ordinarily based upon relational database management frameworks. Ongoing years have seen a sensational increment in the amount of information created by running projects that extends in this area. While it took over ten years, roughly three billion USD, and in excess of 200 gatherings worldwide to collect the main human genome, the present sequencing machines create a similar amount of crude information in seven days, at an expense of around 2000 USD, and on a solitary gadget. A few national and international projects presently manage a huge number of genomes, and patterns like personalized drug call for endeavors to sequence the whole population. In this blog, we feature difficulties that rise up out of this surge of data, for example, parallelization of calculations, compression of genomic sequences, and cloud-based execution of complex scientific work processes. We likewise point to various further difficulties that lie ahead because of the expanding interest in translational medication, i.e., the quickened change of biomedical research results into medical practice.
International Journal of Collaborative Research on Internal Medicine and Public health broadcasts peer-reviewed content covering a wide range of non-surgical clinical aspects which includes disease prognosis, pathological manifestations and medical counseling. The journal lays special emphasis on contributions that address the emerging challenges in the diagnosis and clinical investigation of complex and important diseases in adults that necessitate a cross-specialization approach.
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