Literature DB >> 24972645

Transcriptomics and proteomics in stem cell research.

Hai Wang1, Qian Zhang, Xiangdong Fang.   

Abstract

Stem cells are capable of self-renewal and differentiation, and the processes regulating these events are among the most comprehensively investigated topics in life sciences. In particular, the molecular mechanisms of the self-renewal, proliferation, and differentiation of stem cells have been extensively examined. Multi-omics integrative analysis, such as transcriptomics combined with proteomics, is one of the most promising approaches to the systemic investigation of stem cell biology. We reviewed the available information on stem cells by examining published results using transcriptomic and proteomic characterization of the different stem cell processes. Comprehensive understanding of these important processes can only be achieved using a systemic methodology, and employing such method will strengthen the study on stem cell biology and promote the clinical applications of stem cells.

Mesh:

Year:  2014        PMID: 24972645     DOI: 10.1007/s11684-014-0336-0

Source DB:  PubMed          Journal:  Front Med        ISSN: 2095-0217            Impact factor:   4.592


  105 in total

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Authors:  Lin He; Gregory J Hannon
Journal:  Nat Rev Genet       Date:  2004-07       Impact factor: 53.242

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Authors:  Douglas H Phanstiel; Justin Brumbaugh; Craig D Wenger; Shulan Tian; Mitchell D Probasco; Derek J Bailey; Danielle L Swaney; Mark A Tervo; Jennifer M Bolin; Victor Ruotti; Ron Stewart; James A Thomson; Joshua J Coon
Journal:  Nat Methods       Date:  2011-09-11       Impact factor: 28.547

4.  Phosphorylation dynamics during early differentiation of human embryonic stem cells.

Authors:  Dennis Van Hoof; Javier Muñoz; Stefan R Braam; Martijn W H Pinkse; Rune Linding; Albert J R Heck; Christine L Mummery; Jeroen Krijgsveld
Journal:  Cell Stem Cell       Date:  2009-08-07       Impact factor: 24.633

5.  Discovery of a cytokine and its receptor by functional screening of the extracellular proteome.

Authors:  Haishan Lin; Ernestine Lee; Kevin Hestir; Cindy Leo; Minmei Huang; Elizabeth Bosch; Robert Halenbeck; Ge Wu; Aileen Zhou; Dirk Behrens; Diane Hollenbaugh; Thomas Linnemann; Minmin Qin; Justin Wong; Keting Chu; Stephen K Doberstein; Lewis T Williams
Journal:  Science       Date:  2008-05-09       Impact factor: 47.728

Review 6.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

7.  ESCAPE: database for integrating high-content published data collected from human and mouse embryonic stem cells.

Authors:  Huilei Xu; Caroline Baroukh; Ruth Dannenfelser; Edward Y Chen; Christopher M Tan; Yan Kou; Yujin E Kim; Ihor R Lemischka; Avi Ma'ayan
Journal:  Database (Oxford)       Date:  2013-06-21       Impact factor: 3.451

8.  Genomics and proteomics in stem cell research: the road ahead.

Authors:  Sung-Min Ahn; Richard Simpson; Bonghee Lee
Journal:  Anat Cell Biol       Date:  2010-03-31

9.  i-Tracker: for quantitative proteomics using iTRAQ.

Authors:  Ian P Shadforth; Tom P J Dunkley; Kathryn S Lilley; Conrad Bessant
Journal:  BMC Genomics       Date:  2005-10-20       Impact factor: 3.969

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Authors:  Doron Betel; Manda Wilson; Aaron Gabow; Debora S Marks; Chris Sander
Journal:  Nucleic Acids Res       Date:  2007-12-23       Impact factor: 16.971

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  2 in total

Review 1.  Systems-based technologies in profiling the stem cell molecular framework for cardioregenerative medicine.

Authors:  Saranya P Wyles; Randolph S Faustino; Xing Li; Andre Terzic; Timothy J Nelson
Journal:  Stem Cell Rev Rep       Date:  2015-06       Impact factor: 5.739

Review 2.  Web resources for stem cell research.

Authors:  Ting Wei; Xing Peng; Lili Ye; Jiajia Wang; Fuhai Song; Zhouxian Bai; Guangchun Han; Fengmin Ji; Hongxing Lei
Journal:  Genomics Proteomics Bioinformatics       Date:  2015-02-18       Impact factor: 7.691

  2 in total

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