Literature DB >> 19273085

Methods for quantitation of gene expression.

Vigdis Nygaard1, Eivind Hovig.   

Abstract

Gene expression of protein encoding genes can be quantitatively measured at the transcriptional level by a number of low- to high-throughput methods. The sensitivity of each method is dependent on both the intrinsic properties of the respective technology and the absolute number of each mRNA molecule to be measured. For these reasons, the correlation of measurements between technological platforms may be variable. Due to the complexity of the transcriptome, the purpose of a gene expression study dictates the choice of method as each is connected to a set of advantages and disadvantages. Strategies such as global mRNA amplification of small samples, have been implemented to overcome previous limitations. However, stochastic events will limit quantitative measurements of any tool when in-put levels are extremely low. Due to the versatile nature of microarray technology, this method will likely persist as a highly applied tool to query the levels of non-coding transcripts, a new expansion in the field of gene expression analysis although possible advances of the technology may occur.

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Year:  2009        PMID: 19273085     DOI: 10.2741/3262

Source DB:  PubMed          Journal:  Front Biosci (Landmark Ed)        ISSN: 2768-6698


  9 in total

1.  Selection of reference genes for quantitative real time RT-PCR during dimorphism in the zygomycete Mucor circinelloides.

Authors:  Marco I Valle-Maldonado; Irvin E Jácome-Galarza; Félix Gutiérrez-Corona; Martha I Ramírez-Díaz; Jesús Campos-García; Víctor Meza-Carmen
Journal:  Mol Biol Rep       Date:  2014-11-13       Impact factor: 2.316

2.  Identifying individual DNA species in a complex mixture by precisely measuring the spacing between nicking restriction enzymes with atomic force microscope.

Authors:  Jason Reed; Carlin Hsueh; Miu-Ling Lam; Rachel Kjolby; Andrew Sundstrom; Bud Mishra; J K Gimzewski
Journal:  J R Soc Interface       Date:  2012-03-28       Impact factor: 4.118

Review 3.  Methods for the analysis of transcriptome dynamics.

Authors:  Daniela F Rodrigues; Vera M Costa; Ricardo Silvestre; Maria L Bastos; Félix Carvalho
Journal:  Toxicol Res (Camb)       Date:  2019-07-26       Impact factor: 3.524

Review 4.  Apprehending multicellularity: regulatory networks, genomics, and evolution.

Authors:  L Aravind; Vivek Anantharaman; Thiago M Venancio
Journal:  Birth Defects Res C Embryo Today       Date:  2009-06

5.  Identification of differently expressed genes in chemical carcinogen-induced rat bladder cancers.

Authors:  Guangfu Chen; Franky L Chan; Xu Zhang; Peter S F Chan
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2009-04-28

6.  Moutan Cortex Radicis inhibits inflammatory changes of gene expression in lipopolysaccharide-stimulated gingival fibroblasts.

Authors:  Cheol-Sang Yun; Yeong-Gon Choi; Mi-Young Jeong; Je-Hyun Lee; Sabina Lim
Journal:  J Nat Med       Date:  2012-10-20       Impact factor: 2.343

7.  Validation and application of normalization factors for gene expression studies in rubella virus-infected cell lines with quantitative real-time PCR.

Authors:  S Chey; C Claus; U G Liebert
Journal:  J Cell Biochem       Date:  2010-05       Impact factor: 4.429

8.  Valid gene expression normalization by RT-qPCR in studies on hPDL fibroblasts with focus on orthodontic tooth movement and periodontitis.

Authors:  Christian Kirschneck; Sarah Batschkus; Peter Proff; Josef Köstler; Gerrit Spanier; Agnes Schröder
Journal:  Sci Rep       Date:  2017-11-07       Impact factor: 4.379

9.  Pathway analysis identifies altered mitochondrial metabolism, neurotransmission, structural pathways and complement cascade in retina/RPE/ choroid in chick model of form-deprivation myopia.

Authors:  Loretta Giummarra; Sheila G Crewther; Nina Riddell; Melanie J Murphy; David P Crewther
Journal:  PeerJ       Date:  2018-06-27       Impact factor: 2.984

  9 in total

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