Literature DB >> 23020966

Transcriptome analysis using next-generation sequencing.

Kai-Oliver Mutz1, Alexandra Heilkenbrinker, Maren Lönne, Johanna-Gabriela Walter, Frank Stahl.   

Abstract

Up to date research in biology, biotechnology, and medicine requires fast genome and transcriptome analysis technologies for the investigation of cellular state, physiology, and activity. Here, microarray technology and next generation sequencing of transcripts (RNA-Seq) are state of the art. Since microarray technology is limited towards the amount of RNA, the quantification of transcript levels and the sequence information, RNA-Seq provides nearly unlimited possibilities in modern bioanalysis. This chapter presents a detailed description of next-generation sequencing (NGS), describes the impact of this technology on transcriptome analysis and explains its possibilities to explore the modern RNA world.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23020966     DOI: 10.1016/j.copbio.2012.09.004

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  148 in total

1.  RNA-seq in Pulmonary Medicine: How Much Is Enough?

Authors:  Mondira Ray; William Horne; Jeremy P McAleer; David M Ricks; James L Kreindler; Michael S Fitzsimons; Patricia P Chan; Giraldina Trevejo-Nunez; Kong Chen; Merritt Fajt; Wei Chen; Anuradha Ray; Sally Wenzel; Jay K Kolls
Journal:  Am J Respir Crit Care Med       Date:  2015-08-01       Impact factor: 21.405

2.  Lactobacillus reuteri-specific immunoregulatory gene rsiR modulates histamine production and immunomodulation by Lactobacillus reuteri.

Authors:  P Hemarajata; C Gao; K J Pflughoeft; C M Thomas; D M Saulnier; J K Spinler; J Versalovic
Journal:  J Bacteriol       Date:  2013-10-11       Impact factor: 3.490

Review 3.  What can we learn from the transcriptome of the resurrection plant Craterostigma plantagineum?

Authors:  Valentino Giarola; Dorothea Bartels
Journal:  Planta       Date:  2015-05-22       Impact factor: 4.116

4.  Transcriptomic architecture of the adjacent airway field cancerization in non-small cell lung cancer.

Authors:  Humam Kadara; Junya Fujimoto; Suk-Young Yoo; Yuho Maki; Adam C Gower; Mohamed Kabbout; Melinda M Garcia; Chi-Wan Chow; Zuoming Chu; Gabriella Mendoza; Li Shen; Neda Kalhor; Waun Ki Hong; Cesar Moran; Jing Wang; Avrum Spira; Kevin R Coombes; Ignacio I Wistuba
Journal:  J Natl Cancer Inst       Date:  2014-02-22       Impact factor: 13.506

5.  Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing.

Authors:  Nathan P Manes; Bastian R Angermann; Marijke Koppenol-Raab; Eunkyung An; Virginie H Sjoelund; Jing Sun; Masaru Ishii; Ronald N Germain; Martin Meier-Schellersheim; Aleksandra Nita-Lazar
Journal:  Mol Cell Proteomics       Date:  2015-07-21       Impact factor: 5.911

Review 6.  Is it useful to use several "omics" for obtaining valuable results?

Authors:  Magdalena Zapalska-Sozoniuk; Lukasz Chrobak; Krzysztof Kowalczyk; Marta Kankofer
Journal:  Mol Biol Rep       Date:  2019-04-15       Impact factor: 2.316

7.  Application of quantitative trait locus mapping and transcriptomics to studies of the senescence-accelerated phenotype in rats.

Authors:  Elena E Korbolina; Nikita I Ershov; Leonid O Bryzgalov; Natalia G Kolosova
Journal:  BMC Genomics       Date:  2014-12-19       Impact factor: 3.969

8.  Global transcriptome analyses of human and murine terminal erythroid differentiation.

Authors:  Xiuli An; Vincent P Schulz; Jie Li; Kunlu Wu; Jing Liu; Fumin Xue; Jingping Hu; Narla Mohandas; Patrick G Gallagher
Journal:  Blood       Date:  2014-03-17       Impact factor: 22.113

9.  Next generation sequencing data for use in risk assessment.

Authors:  B Alex Merrick
Journal:  Curr Opin Toxicol       Date:  2019-03-08

Review 10.  The pancreatic β-cell transcriptome and integrated-omics.

Authors:  David M Blodgett; Anthony J Cura; David M Harlan
Journal:  Curr Opin Endocrinol Diabetes Obes       Date:  2014-04       Impact factor: 3.243

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