Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics
There 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 p...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-02-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2019.00049/full |
| _version_ | 1819275193454952448 |
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| author | Pawel Suwinski ChuangKee Ong ChuangKee Ong Maurice H. T. Ling Yang Ming Poh Asif M. Khan Asif M. Khan Hui San Ong |
| author_facet | Pawel Suwinski ChuangKee Ong ChuangKee Ong Maurice H. T. Ling Yang Ming Poh Asif M. Khan Asif M. Khan Hui San Ong |
| author_sort | Pawel Suwinski |
| collection | DOAJ |
| description | There 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. |
| first_indexed | 2024-12-23T23:20:26Z |
| format | Article |
| id | doaj.art-c2deee390710499fbcf0ebbd8f20fe83 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-23T23:20:26Z |
| publishDate | 2019-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-c2deee390710499fbcf0ebbd8f20fe832022-12-21T17:26:21ZengFrontiers Media S.A.Frontiers in Genetics1664-80212019-02-011010.3389/fgene.2019.00049422886Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data AnalyticsPawel Suwinski0ChuangKee Ong1ChuangKee Ong2Maurice H. T. Ling3Yang Ming Poh4Asif M. Khan5Asif M. Khan6Hui San Ong7Malaysian Genomics Resource Centre Berhad, Kuala Lumpur, MalaysiaCentre for Bioinformatics, School of Data Sciences, Perdana University, Serdang, MalaysiaCentre of Genomics Research, Precision Medicine and Genomics, AstraZeneca UK Limited, London, United KingdomCentre for Bioinformatics, School of Data Sciences, Perdana University, Serdang, MalaysiaCentre for Bioinformatics, School of Data Sciences, Perdana University, Serdang, MalaysiaCentre for Bioinformatics, School of Data Sciences, Perdana University, Serdang, MalaysiaGraduate School of Medicine, Perdana University, Serdang, MalaysiaCentre for Bioinformatics, School of Data Sciences, Perdana University, Serdang, MalaysiaThere 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.https://www.frontiersin.org/article/10.3389/fgene.2019.00049/fullbig dataexomepersonalized medicinesequencingprecisionanalytics |
| spellingShingle | Pawel Suwinski ChuangKee Ong ChuangKee Ong Maurice H. T. Ling Yang Ming Poh Asif M. Khan Asif M. Khan Hui San Ong Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics Frontiers in Genetics big data exome personalized medicine sequencing precision analytics |
| title | Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics |
| title_full | Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics |
| title_fullStr | Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics |
| title_full_unstemmed | Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics |
| title_short | Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics |
| title_sort | advancing personalized medicine through the application of whole exome sequencing and big data analytics |
| topic | big data exome personalized medicine sequencing precision analytics |
| url | https://www.frontiersin.org/article/10.3389/fgene.2019.00049/full |
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