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A proteomic profiling dataset of recombinant Chinese hamster ovary cells showing enhanced cellular growth following miR-378 depletion.
Coleman, Orla; Costello, Alan; Henry, Michael; Lao, Nga T; Barron, Niall; Clynes, Martin; Meleady, Paula.
Afiliação
  • Coleman O; National Institute for Cellular Biotechnology, Dublin City University, Dublin 9, Ireland.
  • Costello A; National Institute for Cellular Biotechnology, Dublin City University, Dublin 9, Ireland.
  • Henry M; National Institute for Cellular Biotechnology, Dublin City University, Dublin 9, Ireland.
  • Lao NT; National Institute for Cellular Biotechnology, Dublin City University, Dublin 9, Ireland.
  • Barron N; National Institute for Bioprocess Research and Training, Blackrock Co., Dublin, Ireland.
  • Clynes M; University College Dublin, Belfield, Dublin 4, Ireland.
  • Meleady P; National Institute for Cellular Biotechnology, Dublin City University, Dublin 9, Ireland.
Data Brief ; 21: 2679-2688, 2018 Dec.
Article em En | MEDLINE | ID: mdl-30761351
ABSTRACT
The proteomic data presented in this article provide supporting information to the related research article "Depletion of endogenous miRNA-378-3p increases peak cell density of CHO DP12 cells and is correlated with elevated levels of Ubiquitin Carboxyl-Terminal Hydrolase 14" (Costello et al., in press) [1]. Control and microRNA-378 depleted CHO DP12 cells were profiled using label-free quantitative proteomic profiling. CHO DP12 cells were collected on day 4 and 8 of batch culture, subcellular proteomic enrichment was performed, and subsequent fractions were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Here we provide the complete proteomic dataset of proteins significantly differentially expressed by greater than 1.25-fold change in abundance between control and miR-378 depleted CHO DP12 cells, and the lists of all identified proteins for each condition.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2018 Tipo de documento: Article