Literature DB >> 18370228

Applications of microarrays and biochips in pharmacogenomics.

Gary Hardiman1.   

Abstract

The complete sequence of the human genome and subsequent intensive searches for polymorphic variations are providing the prerequisite markers necessary to facilitate elucidation of the genetic variability in drug responses. Improvements in the sensitivity and precision of DNA microarrays permit a detailed and accurate scrutiny of the human genome. These advances have the potential to significantly improve health care management by improving disease diagnosis and targeting molecular therapy. Pharmacogenetic approaches, in limited use today, will become an integral part of therapeutic monitoring and health management, permitting patient stratification in advance of treatments, with the potential to eliminate adverse drug reactions. In this chapter, the current state of biochip technology is discussed, and recent applications in the arena of clinic diagnostics are explored.

Entities:  

Mesh:

Year:  2008        PMID: 18370228     DOI: 10.1007/978-1-59745-205-2_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

1.  Alternative reliable method for cytochrome P450 2D6 poor metabolizers genotyping.

Authors:  E Pindurová; A Zourková; J Zrůstová; J Juřica; A Pavelka
Journal:  Mol Biotechnol       Date:  2013-01       Impact factor: 2.695

2.  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

3.  Non-gaussian distributions affect identification of expression patterns, functional annotation, and prospective classification in human cancer genomes.

Authors:  Nicholas F Marko; Robert J Weil
Journal:  PLoS One       Date:  2012-10-31       Impact factor: 3.240

4.  An Introduction to Systems Analytics and Integration of Big Omics Data.

Authors:  Gary Hardiman
Journal:  Genes (Basel)       Date:  2020-02-26       Impact factor: 4.096

  4 in total

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