Literature DB >> 27066891

Next generation sequencing: implications in personalized medicine and pharmacogenomics.

Bahareh Rabbani1, Hirofumi Nakaoka2, Shahin Akhondzadeh3, Mustafa Tekin4, Nejat Mahdieh1.   

Abstract

A breakthrough in next generation sequencing (NGS) in the last decade provided an unprecedented opportunity to investigate genetic variations in humans and their roles in health and disease. NGS offers regional genomic sequencing such as whole exome sequencing of coding regions of all genes, as well as whole genome sequencing. RNA-seq offers sequencing of the entire transcriptome and ChIP-seq allows for sequencing the epigenetic architecture of the genome. Identifying genetic variations in individuals can be used to predict disease risk, with the potential to halt or retard disease progression. NGS can also be used to predict the response to or adverse effects of drugs or to calculate appropriate drug dosage. Such a personalized medicine also provides the possibility to treat diseases based on the genetic makeup of the patient. Here, we review the basics of NGS technologies and their application in human diseases to foster human healthcare and personalized medicine.

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Mesh:

Year:  2016        PMID: 27066891     DOI: 10.1039/c6mb00115g

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  32 in total

1.  Implementation and obstacles of pharmacogenetics in clinical practice: An international survey.

Authors:  Elizabeth Abou Diwan; Ralph I Zeitoun; Lea Abou Haidar; Ingolf Cascorbi; Nathalie Khoueiry Zgheib
Journal:  Br J Clin Pharmacol       Date:  2019-07-07       Impact factor: 4.335

2.  Performance comparison: exome sequencing as a single test replacing Sanger sequencing.

Authors:  Hila Fridman; Concetta Bormans; Moshe Einhorn; Daniel Au; Arjan Bormans; Yuval Porat; Luisa Fernanda Sanchez; Brent Manning; Ephrat Levy-Lahad; Doron M Behar
Journal:  Mol Genet Genomics       Date:  2021-03-11       Impact factor: 3.291

Review 3.  Role of pharmacogenetics in public health and clinical health care: a SWOT analysis.

Authors:  Ritika Kapoor; Wei Chuen Tan-Koi; Yik-Ying Teo
Journal:  Eur J Hum Genet       Date:  2016-08-31       Impact factor: 4.246

4.  Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning.

Authors:  Arun Prasad Pandurangan; Tom L Blundell
Journal:  Protein Sci       Date:  2019-11-25       Impact factor: 6.725

Review 5.  Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues.

Authors:  Aleksandra Karolak; Dmitry A Markov; Lisa J McCawley; Katarzyna A Rejniak
Journal:  J R Soc Interface       Date:  2018-01       Impact factor: 4.118

6.  MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules.

Authors:  Paolo Martini; Monica Chiogna; Enrica Calura; Chiara Romualdi
Journal:  Nucleic Acids Res       Date:  2019-08-22       Impact factor: 16.971

7.  Sudden Arrhythmic Death During Exercise: A Post-Mortem Genetic Analysis.

Authors:  Oscar Campuzano; Olallo Sanchez-Molero; Anna Fernandez; Irene Mademont-Soler; Monica Coll; Alexandra Perez-Serra; Jesus Mates; Bernat Del Olmo; Ferran Pico; Laia Nogue-Navarro; Georgia Sarquella-Brugada; Anna Iglesias; Sergi Cesar; Esther Carro; Juan Carlos Borondo; Josep Brugada; Josep Castellà; Jordi Medallo; Ramon Brugada
Journal:  Sports Med       Date:  2017-10       Impact factor: 11.136

8.  Machine-learning of complex evolutionary signals improves classification of SNVs.

Authors:  Sapir Labes; Doron Stupp; Naama Wagner; Idit Bloch; Michal Lotem; Ephrat L Lahad; Paz Polak; Tal Pupko; Yuval Tabach
Journal:  NAR Genom Bioinform       Date:  2022-04-07

Review 9.  Covalent labeling of nucleic acids.

Authors:  Nils Klöcker; Florian P Weissenboeck; Andrea Rentmeister
Journal:  Chem Soc Rev       Date:  2020-10-21       Impact factor: 54.564

10.  SDM: a server for predicting effects of mutations on protein stability.

Authors:  Arun Prasad Pandurangan; Bernardo Ochoa-Montaño; David B Ascher; Tom L Blundell
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

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