MS-BID: A Java package for label-free LC-MS-based comparative proteomic analysis

Daehee Hwang; Ning Zhang; Hookeun Lee; Eugene Yi; Hui Zhang; Inyoul Y. Lee; Leroy Hood; Ruedi Aebersold

doi:10.1093/bioinformatics/btn491

MS-BID: A Java package for label-free LC-MS-based comparative proteomic analysis

Daehee Hwang, Ning Zhang, Hookeun Lee, Eugene Yi, Hui Zhang, Inyoul Y. Lee, Leroy Hood, Ruedi Aebersold

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Summary: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples.

Original language	English (US)
Pages (from-to)	2641-2642
Number of pages	2
Journal	Bioinformatics
Volume	24
Issue number	22
DOIs	https://doi.org/10.1093/bioinformatics/btn491
State	Published - Nov 2008
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btn491

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@article{1435cab06d1045ea9cdbf9166cfe23bb,

title = "MS-BID: A Java package for label-free LC-MS-based comparative proteomic analysis",

abstract = "Summary: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples.",

author = "Daehee Hwang and Ning Zhang and Hookeun Lee and Eugene Yi and Hui Zhang and Lee, {Inyoul Y.} and Leroy Hood and Ruedi Aebersold",

note = "Funding Information: Funding: National Institutes of Health (grant NS41997, NHLBI grant N01-HV-28179); DOD (grant DAMD17-3-1-0321); KOSEF (grants R15-2004-033-07002-0 and M1AN29-2008-04112); KRF-2007-331-C00204.",

year = "2008",

month = nov,

doi = "10.1093/bioinformatics/btn491",

language = "English (US)",

volume = "24",

pages = "2641--2642",

journal = "Bioinformatics",

issn = "1367-4803",

publisher = "Oxford University Press",

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T1 - MS-BID

T2 - A Java package for label-free LC-MS-based comparative proteomic analysis

AU - Hwang, Daehee

AU - Zhang, Ning

AU - Lee, Hookeun

AU - Yi, Eugene

AU - Zhang, Hui

AU - Lee, Inyoul Y.

AU - Hood, Leroy

AU - Aebersold, Ruedi

N1 - Funding Information: Funding: National Institutes of Health (grant NS41997, NHLBI grant N01-HV-28179); DOD (grant DAMD17-3-1-0321); KOSEF (grants R15-2004-033-07002-0 and M1AN29-2008-04112); KRF-2007-331-C00204.

PY - 2008/11

Y1 - 2008/11

N2 - Summary: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples.

AB - Summary: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples.

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ER -

MS-BID: A Java package for label-free LC-MS-based comparative proteomic analysis

Abstract

ASJC Scopus subject areas

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