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Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics

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dc.contributor.authorSuwinski, Pawel
dc.contributor.authorOng, ChuangKee
dc.contributor.authorLing, Maurice H. T.
dc.contributor.authorPoh, Yang Ming
dc.contributor.authorKhan, Asif M.
dc.contributor.authorOng, Hui San
dc.contributor.institutionauthorKHAN, MOHAMMAD ASİF
dc.date.accessioned2021-08-31T20:59:09Z
dc.date.available2021-08-31T20:59:09Z
dc.date.issued2019-02-01T00:00:00Z
dc.description.abstractThere is a growing attention toward personalized medicine. This is led by a fundamental shift from the -one size fits all- paradigm for treatment of patients with conditions or predisposition to diseases, to one that embraces novel approaches, such as tailored target therapies, to achieve the best possible outcomes. Driven by these, several national and international genome projects have been initiated to reap the benefits of personalized medicine. Exome and targeted sequencing provide a balance between cost and benefit, in contrast to whole genome sequencing (WGS). Whole exome sequencing (WES) targets approximately 3% of the whole genome, which is the basis for protein-coding genes. Nonetheless, it has the characteristics of big data in large deployment. Herein, the application of WES and its relevance in advancing personalized medicine is reviewed. WES is mapped to Big Data -10 Vs- and the resulting challenges discussed. Application of existing biological databases and bioinformatics tools to address the bottleneck in data processing and analysis are presented, including the need for new generation big data analytics for the multi-omics challenges of personalized medicine. This includes the incorporation of artificial intelligence (AI) in the clinical utility landscape of genomic information, and future consideration to create a new frontier toward advancing the field of personalized medicine.
dc.identifier.citationSuwinski P., Ong C., Ling M. H. T. , Poh Y. M. , Khan A. M. , Ong H. S. , -Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics-, FRONTIERS IN GENETICS, cilt.10, 2019
dc.identifier.doi10.3389/fgene.2019.00049
dc.identifier.scopus85065964263
dc.identifier.urihttp://hdl.handle.net/20.500.12645/29300
dc.identifier.wosWOS:000458600900001
dc.titleAdvancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics
dc.typeArticle
dspace.entity.typePublication
local.avesis.id111d0f49-f43a-46b8-b34b-c8881afb2ebc
local.publication.isinternational1
relation.isAuthorOfPublication60fee672-8864-4711-ae92-5b9dd3bb0ef7
relation.isAuthorOfPublication.latestForDiscovery60fee672-8864-4711-ae92-5b9dd3bb0ef7
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