Standard Standard

A hierarchical statistical modeling approach to analyze proteomic isobaric tag for relative and absolute quantitation data. / C, Zhou; MJ, Walker; AJ, Williamson et al.
In: Bioinformatics, 15.12.2014, p. 549-558.

Research output: Contribution to journalArticlepeer-review

HarvardHarvard

APA

CBE

MLA

VancouverVancouver

C Z, MJ W, AJ W, A P, C B, C D et al. A hierarchical statistical modeling approach to analyze proteomic isobaric tag for relative and absolute quantitation data. Bioinformatics. 2014 Dec 15;549-558. doi: 10.1093/bioinformatics/btt722

Author

C, Zhou ; MJ, Walker ; AJ, Williamson et al. / A hierarchical statistical modeling approach to analyze proteomic isobaric tag for relative and absolute quantitation data. In: Bioinformatics. 2014 ; pp. 549-558.

RIS

TY - JOUR

T1 - A hierarchical statistical modeling approach to analyze proteomic isobaric tag for relative and absolute quantitation data.

AU - C, Zhou

AU - MJ, Walker

AU - AJ, Williamson

AU - A, Pierce

AU - C, Berzuini

AU - C, Dive

AU - AD, Whetton

PY - 2014/12/15

Y1 - 2014/12/15

U2 - 10.1093/bioinformatics/btt722

DO - 10.1093/bioinformatics/btt722

M3 - Article

SP - 549

EP - 558

JO - Bioinformatics

JF - Bioinformatics

SN - 1460-2059

ER -