title: Statistical contributions to proteomic research.
abstract: Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the key statistical principles that should guide the experimental design and analysis of such studies.
authors.affiliation: Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: Morris
authors.forename: Keith A
authors.initials: KA
authors.lastname: Baggerly
authors.forename: Howard B
authors.initials: HB
authors.lastname: Gutstein
authors.forename: Kevin R
authors.initials: KR
authors.lastname: Coombes
mesh_terms: D015415:Biomarkers / Q000652:urine; D005260:Female; D006801:Humans; D007834:Lasers; D009369:Neoplasms / Q000378:metabolism / Q000652:urine; D040901:Proteomics / Q000706:statistics & numerical data*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D015415:Biomarkers
references.citation: Cancer Res. 2004 Aug 15;64(16):5882-90
references.pmid: 15313933
references.citation: Endocr Relat Cancer. 2004 Jun;11(2):163-78
references.pmid: 15163296
references.citation: Brief Funct Genomic Proteomic. 2005 Feb;3(4):322-31
references.pmid: 15814023
references.citation: Bioinformatics. 2004 Mar 22;20(5):777-85
references.pmid: 14751995
references.citation: Endocr Relat Cancer. 2004 Dec;11(4):583-4; author reply 585-7
references.pmid: 15613439
references.citation: Proteomics. 2003 Sep;3(9):1667-72
references.pmid: 12973722
references.citation: Lancet. 2002 Feb 16;359(9306):572-7
references.pmid: 11867112
references.citation: Biostatistics. 2004 Apr;5(2):155-76
references.pmid: 15054023
references.citation: Cancer Inform. 2005;1:9-14
references.pmid: 19305627
references.citation: Cancer Inform. 2007 Feb 23;2:313-27
references.pmid: 19458774
references.citation: J Natl Cancer Inst. 2005 Feb 16;97(4):307-9
references.pmid: 15713966
references.citation: Bioinformatics. 2008 Feb 15;24(4):529-36
references.pmid: 18194961
references.citation: J Natl Cancer Inst. 2004 Mar 3;96(5):353-6
references.pmid: 14996856
references.citation: Mol Cell Proteomics. 2004 Apr;3(4):367-78
references.pmid: 14990683
references.citation: Bioinformatics. 2004 Jul 22;20(11):1737-45
references.pmid: 14988112
references.citation: BMC Bioinformatics. 2003 Jun 9;4:24
references.pmid: 12795817
references.citation: Bioinformatics. 2003 Jul 1;19(10):1236-42
references.pmid: 12835267
references.citation: Bioinformatics. 2007 Jan 15;23(2):264-5
references.pmid: 17121773
references.citation: Nat Biotechnol. 2005 Mar;23(3):291-2
references.pmid: 15765078
references.citation: Nat Rev Cancer. 2004 Apr;4(4):309-14
references.pmid: 15057290
references.citation: J Natl Cancer Inst. 2007 Jan 17;99(2):147-57
references.pmid: 17227998
references.citation: Clin Chem. 2003 Oct;49(10):1615-23
references.pmid: 14500586
references.citation: Bioinformatics. 2005 May 1;21(9):1764-75
references.pmid: 15673564
references.citation: Expert Rev Mol Diagn. 2004 Sep;4(5):575-7
references.pmid: 15347249
references.citation: Proteomics. 2005 Nov;5(16):4107-17
references.pmid: 16254928