Literature DB >> 24560816

Is this the real time for genomics?

Maria Guarnaccia1, Giulia Gentile2, Enrico Alessi3, Claudio Schneider4, Salvatore Petralia5, Sebastiano Cavallaro6.   

Abstract

In the last decades, molecular biology has moved from gene-by-gene analysis to more complex studies using a genome-wide scale. Thanks to high-throughput genomic technologies, such as microarrays and next-generation sequencing, a huge amount of information has been generated, expanding our knowledge on the genetic basis of various diseases. Although some of this information could be transferred to clinical diagnostics, the technologies available are not suitable for this purpose. In this review, we will discuss the drawbacks associated with the use of traditional DNA microarrays in diagnostics, pointing out emerging platforms that could overcome these obstacles and offer a more reproducible, qualitative and quantitative multigenic analysis. New miniaturized and automated devices, called Lab-on-Chip, begin to integrate PCR and microarray on the same platform, offering integrated sample-to-result systems. The introduction of this kind of innovative devices may facilitate the transition of genome-based tests into clinical routine.
Copyright © 2014. Published by Elsevier Inc.

Keywords:  Diagnostics; Genome-based tests; Lab-on-Chip; Next-generation sequencing; Point-of-Care; Real-time microarray

Mesh:

Year:  2014        PMID: 24560816     DOI: 10.1016/j.ygeno.2014.02.003

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  8 in total

1.  The metabolic response to a high-fat diet reveals obesity-prone and -resistant phenotypes in mice with distinct mRNA-seq transcriptome profiles.

Authors:  J-Y Choi; R A McGregor; E-Y Kwon; Y J Kim; Y Han; J H Y Park; K W Lee; S-J Kim; J Kim; J W Yun; M-S Choi
Journal:  Int J Obes (Lond)       Date:  2016-05-05       Impact factor: 5.095

Review 2.  Molecular oncology testing in resource-limited settings.

Authors:  Margaret L Gulley; Douglas R Morgan
Journal:  J Mol Diagn       Date:  2014-09-19       Impact factor: 5.568

3.  GFVO: the Genomic Feature and Variation Ontology.

Authors:  Joachim Baran; Bibi Sehnaaz Begum Durgahee; Karen Eilbeck; Erick Antezana; Robert Hoehndorf; Michel Dumontier
Journal:  PeerJ       Date:  2015-05-05       Impact factor: 2.984

4.  Sexual Dimorphism and Aging in the Human Hyppocampus: Identification, Validation, and Impact of Differentially Expressed Genes by Factorial Microarray and Network Analysis.

Authors:  Daniel V Guebel; Néstor V Torres
Journal:  Front Aging Neurosci       Date:  2016-10-05       Impact factor: 5.750

5.  Genotyping of KRAS Mutational Status by the In-Check Lab-on-Chip Platform.

Authors:  Maria Guarnaccia; Rosario Iemmolo; Floriana San Biagio; Enrico Alessi; Sebastiano Cavallaro
Journal:  Sensors (Basel)       Date:  2018-01-05       Impact factor: 3.576

6.  Influence of Glucose Availability and CRP Acetylation on the Genome-Wide Transcriptional Response of Escherichia coli: Assessment by an Optimized Factorial Microarray Analysis.

Authors:  Daniel V Guebel; Néstor V Torres
Journal:  Front Microbiol       Date:  2018-05-23       Impact factor: 5.640

7.  Development of a Pharmacogenetic Lab-on-Chip Assay Based on the In-Check Technology to Screen for Genetic Variations Associated to Adverse Drug Reactions to Common Chemotherapeutic Agents.

Authors:  Rosario Iemmolo; Valentina La Cognata; Giovanna Morello; Maria Guarnaccia; Mariamena Arbitrio; Enrico Alessi; Sebastiano Cavallaro
Journal:  Biosensors (Basel)       Date:  2020-12-09

8.  A Miniaturized Silicon Lab-on-Chip for Integrated PCR and Hybridization Microarray for High Multiplexing Nucleic Acids Analysis.

Authors:  Giorgio Ventimiglia; Massimiliano Pesaturo; Alastair Malcolm; Salvatore Petralia
Journal:  Biosensors (Basel)       Date:  2022-07-25
  8 in total

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