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A mouse plasma peptide atlas as a resource for disease proteomics

Qing Zhang1 email, Rajasree Menon2 email, Eric W Deutsch3 email, Sharon J Pitteri1 email, Vitor M Faca1 email, Hong Wang1 email, Lisa F Newcomb1 email, Ronald A DePinho4,5 email, Nabeel Bardeesy6 email, Daniela Dinulescu7 email, Kenneth E Hung6 email, Raju Kucherlapati6 email, Tyler Jacks8 email, Katerina Politi9 email, Ruedi Aebersold3,10 email, Gilbert S Omenn2 email, David J States2 email and Samir M Hanash1 email

Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA

Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, MI 48109, USA

Institute for Systems Biology, Seattle, WA 98103, USA

Dana-Farber Cancer Institute, Harvard Cancer Center, Boston, MA 02115, USA

Center for Applied Cancer Science, Belfer Institute for Innovative Cancer Science, Department of Medical Oncology, Medicine, Genetics, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02114, USA

Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA

Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA

Center for Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA

10  Institute of Molecular Systems Biology, ETH Zurich and Faculty of Science, University of Zurich, 8093 Zurich, Switzerland

author email corresponding author email

Genome Biology 2008, 9:R93doi:10.1186/gb-2008-9-6-r93

Published: 3 June 2008

Subject areas: Genome studies, Methods, Model organisms

Abstract

We present an in-depth analysis of mouse plasma leading to the development of a publicly available repository composed of 568 liquid chromatography-tandem mass spectrometry runs. A total of 13,779 distinct peptides have been identified with high confidence. The corresponding approximately 3,000 proteins are estimated to span a 7 logarithmic range of abundance in plasma. A major finding from this study is the identification of novel isoforms and transcript variants not previously predicted from genome analysis.


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