J
Jun Peng
Researcher at University of Alberta
Publications - 10
Citations - 3435
Jun Peng is an academic researcher from University of Alberta. The author has contributed to research in topics: Metabolome & Metabolomics. The author has an hindex of 8, co-authored 9 publications receiving 3073 citations. Previous affiliations of Jun Peng include National Institute for Nanotechnology.
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Journal ArticleDOI
HMDB: a knowledgebase for the human metabolome
David S. Wishart,Craig Knox,An Chi Guo,Roman Eisner,Nelson Young,Bijaya Gautam,David Hau,Nick Psychogios,Edison Dong,Souhaila Bouatra,Rupasri Mandal,Igor Sinelnikov,Jianguo Xia,Leslie Jia,Joseph A. Cruz,Emilia L. Lim,Constance A. Sobsey,Savita Shrivastava,Paul Huang,Philip Liu,Lydia Fang,Jun Peng,Ryan Fradette,Dean Cheng,Dan Tzur,Melisa Clements,Avalyn Lewis,Andrea De Souza,Azaret Zuniga,Margot Dawe,Yeping Xiong,Derrick L. J. Clive,Russell Greiner,Alsu Nazyrova,Rustem Shaykhutdinov,Liang Li,Hans J. Vogel,Ian J. Forsythe +37 more
TL;DR: The most recent release of HMDB has been significantly expanded and enhanced over the previous release, with the number of fully annotated metabolite entries growing from 2180 to more than 6800, a 300% increase.
Journal ArticleDOI
The Human Serum Metabolome
Nikolaos Psychogios,David Hau,Jun Peng,An Chi Guo,Rupasri Mandal,Souhaila Bouatra,Igor Sinelnikov,Ramanarayan Krishnamurthy,Roman Eisner,Bijaya Gautam,Nelson Young,Jianguo Xia,Craig Knox,Edison Dong,Paul Huang,Zsuzsanna Hollander,Theresa L. Pedersen,Steven R. Smith,Fiona Bamforth,Russell Greiner,Bruce M. McManus,John W. Newman,Theodore L. Goodfriend,David S. Wishart,David S. Wishart +24 more
TL;DR: This work has combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome.
Journal ArticleDOI
Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.
TL;DR: The UMS method was developed and applied for a urine metabolomics study of bladder cancer and showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples.
Journal ArticleDOI
Development of isotope labeling liquid chromatography mass spectrometry for mouse urine metabolomics: quantitative metabolomic study of transgenic mice related to Alzheimer's disease
Jun Peng,Kevin Guo,Jianguo Xia,Jianjun Zhou,Jing Yang,David Westaway,David S. Wishart,Liang Li +7 more
TL;DR: An enabling method based on differential isotope labeling liquid chromatography mass spectrometry (LC-MS) for relative quantification of over 950 putative metabolites using 20 μL of urine as the starting material is reported, illustrating the utility of this isotope labeled LC-MS method for biomarker discovery using mouse urine metabolomics.
Journal ArticleDOI
Liquid–liquid extraction combined with differential isotope dimethylaminophenacyl labeling for improved metabolomic profiling of organic acids
TL;DR: An improved method based on the use of liquid-liquid extraction to selectively extract the organic acids, followed by using differential isotope p-dimethylaminophenacyl (DmPA) labeling of the acid metabolites to generate a very comprehensive profile of the organic acid sub-metabolome is reported.