Bioinformatics strategies for proteomic profiling

C. Nicole White; Daniel W. Chan; Zhen Zhang

doi:10.1016/j.clinbiochem.2004.05.004

Bioinformatics strategies for proteomic profiling

C. Nicole White, Daniel W. Chan, Zhen Zhang

School of Medicine

Research output: Contribution to journal › Review article › peer-review

54 Scopus citations

Abstract

Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.

Original language	English (US)
Pages (from-to)	636-641
Number of pages	6
Journal	Clinical Biochemistry
Volume	37
Issue number	7
DOIs	https://doi.org/10.1016/j.clinbiochem.2004.05.004
State	Published - Jul 2004

Keywords

Bioinformatics
Mass spectrometry
Proteomic profiling
Quality control
SELDI

ASJC Scopus subject areas

Clinical Biochemistry

Access to Document

10.1016/j.clinbiochem.2004.05.004

Cite this

@article{2f3852d5ff3348a7b12391eddb40b8da,

title = "Bioinformatics strategies for proteomic profiling",

abstract = "Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.",

keywords = "Bioinformatics, Mass spectrometry, Proteomic profiling, Quality control, SELDI",

author = "White, {C. Nicole} and Chan, {Daniel W.} and Zhen Zhang",

note = "Funding Information: This work was supported in part by a grant from Ciphergen Biosystems, Inc. (Fremont, CA), and by an NCI Grant 1P50 CA83639, UTMDACC Specialized Programs of Research Excellence (SPORE) in Ovarian Cancer. We would also like to thank Lori Sokoll for her assistance in reviewing the article.",

year = "2004",

month = jul,

doi = "10.1016/j.clinbiochem.2004.05.004",

language = "English (US)",

volume = "37",

pages = "636--641",

journal = "Clinical Biochemistry",

issn = "0009-9120",

publisher = "Elsevier Inc.",

number = "7",

}

TY - JOUR

T1 - Bioinformatics strategies for proteomic profiling

AU - White, C. Nicole

AU - Chan, Daniel W.

AU - Zhang, Zhen

N1 - Funding Information: This work was supported in part by a grant from Ciphergen Biosystems, Inc. (Fremont, CA), and by an NCI Grant 1P50 CA83639, UTMDACC Specialized Programs of Research Excellence (SPORE) in Ovarian Cancer. We would also like to thank Lori Sokoll for her assistance in reviewing the article.

PY - 2004/7

Y1 - 2004/7

N2 - Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.

AB - Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.

KW - Bioinformatics

KW - Mass spectrometry

KW - Proteomic profiling

KW - Quality control

KW - SELDI

UR - http://www.scopus.com/inward/record.url?scp=3042541639&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=3042541639&partnerID=8YFLogxK

U2 - 10.1016/j.clinbiochem.2004.05.004

DO - 10.1016/j.clinbiochem.2004.05.004

M3 - Review article

C2 - 15234244

AN - SCOPUS:3042541639

SN - 0009-9120

VL - 37

SP - 636

EP - 641

JO - Clinical Biochemistry

JF - Clinical Biochemistry

IS - 7

ER -

Bioinformatics strategies for proteomic profiling

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this