Classification of mass spectrometry based protein markers by kriging error matching

Tuan D. Pham; Honghui Wang; Xiaobo Zhou; Dominik Beck; Miriam Brandl; Gerard Hoehn; Joseph Azok; Marie Luise Brennan; Stanley L. Hazen; Stephen T.C. Wong

doi:10.1007/978-3-540-70715-8_8

Classification of mass spectrometry based protein markers by kriging error matching

Tuan D. Pham, Honghui Wang, Xiaobo Zhou, Dominik Beck, Miriam Brandl, Gerard Hoehn, Joseph Azok, Marie Luise Brennan, Stanley L. Hazen, Stephen T.C. Wong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Discovery of biomarkers using serum proteomic patterns is currently one of the most attractive interdisciplinary research areas in computational life science. This new proteomic approach has the clinical significance in being able to detect disease in its early stages and to develop new drugs for disease treatment and prevention. This paper introduces a novel pattern classification strategy for identifying protein biomarkers using mass spectrometry data of blood samples collected from patients in emergency department monitored for major adverse cardiac events within six months. We applied the theory of geostatistics and a kriging error matching scheme for identifying protein biomarkers that are able to provide an average classification rate superior to other current methods. The proposed strategy is very promising as a general computational bioinformatic model for proteomic-pattern based biomarker discovery.

Original language	English (US)
Title of host publication	Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings
Pages	82-94
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-540-70715-8_8
State	Published - 2008
Event	3rd International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, MDA 2008 - Leipzig, Germany Duration: Jul 14 2008 → Jul 14 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5108 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	3rd International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, MDA 2008
Country	Germany
City	Leipzig
Period	7/14/08 → 7/14/08

Keywords

Bioinformatics
Biomarker discovery
Geostatistics
Mass spectrometry data
Pattern classification
Proteomics

ASJC Scopus subject areas

Computer Science(all)
Biochemistry, Genetics and Molecular Biology(all)
Theoretical Computer Science

Access to Document

10.1007/978-3-540-70715-8_8

Fingerprint Dive into the research topics of 'Classification of mass spectrometry based protein markers by kriging error matching'. Together they form a unique fingerprint.

Cite this

Pham, T. D., Wang, H., Zhou, X., Beck, D., Brandl, M., Hoehn, G., Azok, J., Brennan, M. L., Hazen, S. L., & Wong, S. T. C. (2008). Classification of mass spectrometry based protein markers by kriging error matching. In Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings (pp. 82-94). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5108 LNAI). https://doi.org/10.1007/978-3-540-70715-8_8

Classification of mass spectrometry based protein markers by kriging error matching. / Pham, Tuan D.; Wang, Honghui; Zhou, Xiaobo; Beck, Dominik; Brandl, Miriam; Hoehn, Gerard; Azok, Joseph; Brennan, Marie Luise; Hazen, Stanley L.; Wong, Stephen T.C.

Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings. 2008. p. 82-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5108 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Pham, TD, Wang, H, Zhou, X, Beck, D, Brandl, M, Hoehn, G, Azok, J, Brennan, ML, Hazen, SL & Wong, STC 2008, Classification of mass spectrometry based protein markers by kriging error matching. in Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5108 LNAI, pp. 82-94, 3rd International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, MDA 2008, Leipzig, Germany, 7/14/08. https://doi.org/10.1007/978-3-540-70715-8_8

Pham TD, Wang H, Zhou X, Beck D, Brandl M, Hoehn G et al. Classification of mass spectrometry based protein markers by kriging error matching. In Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings. 2008. p. 82-94. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-70715-8_8

Pham, Tuan D. ; Wang, Honghui ; Zhou, Xiaobo ; Beck, Dominik ; Brandl, Miriam ; Hoehn, Gerard ; Azok, Joseph ; Brennan, Marie Luise ; Hazen, Stanley L. ; Wong, Stephen T.C. / Classification of mass spectrometry based protein markers by kriging error matching. Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings. 2008. pp. 82-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{a81bf85511d94d5894e29db0d8b2b462,

title = "Classification of mass spectrometry based protein markers by kriging error matching",

abstract = "Discovery of biomarkers using serum proteomic patterns is currently one of the most attractive interdisciplinary research areas in computational life science. This new proteomic approach has the clinical significance in being able to detect disease in its early stages and to develop new drugs for disease treatment and prevention. This paper introduces a novel pattern classification strategy for identifying protein biomarkers using mass spectrometry data of blood samples collected from patients in emergency department monitored for major adverse cardiac events within six months. We applied the theory of geostatistics and a kriging error matching scheme for identifying protein biomarkers that are able to provide an average classification rate superior to other current methods. The proposed strategy is very promising as a general computational bioinformatic model for proteomic-pattern based biomarker discovery.",

keywords = "Bioinformatics, Biomarker discovery, Geostatistics, Mass spectrometry data, Pattern classification, Proteomics",

author = "Pham, {Tuan D.} and Honghui Wang and Xiaobo Zhou and Dominik Beck and Miriam Brandl and Gerard Hoehn and Joseph Azok and Brennan, {Marie Luise} and Hazen, {Stanley L.} and Wong, {Stephen T.C.}",

year = "2008",

doi = "10.1007/978-3-540-70715-8_8",

language = "English (US)",

isbn = "354070714X",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "82--94",

booktitle = "Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings",

note = "3rd International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, MDA 2008 ; Conference date: 14-07-2008 Through 14-07-2008",

}

TY - GEN

T1 - Classification of mass spectrometry based protein markers by kriging error matching

AU - Pham, Tuan D.

AU - Wang, Honghui

AU - Zhou, Xiaobo

AU - Beck, Dominik

AU - Brandl, Miriam

AU - Hoehn, Gerard

AU - Azok, Joseph

AU - Brennan, Marie Luise

AU - Hazen, Stanley L.

AU - Wong, Stephen T.C.

PY - 2008

Y1 - 2008

N2 - Discovery of biomarkers using serum proteomic patterns is currently one of the most attractive interdisciplinary research areas in computational life science. This new proteomic approach has the clinical significance in being able to detect disease in its early stages and to develop new drugs for disease treatment and prevention. This paper introduces a novel pattern classification strategy for identifying protein biomarkers using mass spectrometry data of blood samples collected from patients in emergency department monitored for major adverse cardiac events within six months. We applied the theory of geostatistics and a kriging error matching scheme for identifying protein biomarkers that are able to provide an average classification rate superior to other current methods. The proposed strategy is very promising as a general computational bioinformatic model for proteomic-pattern based biomarker discovery.

AB - Discovery of biomarkers using serum proteomic patterns is currently one of the most attractive interdisciplinary research areas in computational life science. This new proteomic approach has the clinical significance in being able to detect disease in its early stages and to develop new drugs for disease treatment and prevention. This paper introduces a novel pattern classification strategy for identifying protein biomarkers using mass spectrometry data of blood samples collected from patients in emergency department monitored for major adverse cardiac events within six months. We applied the theory of geostatistics and a kriging error matching scheme for identifying protein biomarkers that are able to provide an average classification rate superior to other current methods. The proposed strategy is very promising as a general computational bioinformatic model for proteomic-pattern based biomarker discovery.

KW - Bioinformatics

KW - Biomarker discovery

KW - Geostatistics

KW - Mass spectrometry data

KW - Pattern classification

KW - Proteomics

UR - http://www.scopus.com/inward/record.url?scp=48949089631&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=48949089631&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-70715-8_8

DO - 10.1007/978-3-540-70715-8_8

M3 - Conference contribution

AN - SCOPUS:48949089631

SN - 354070714X

SN - 9783540707141

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 82

EP - 94

BT - Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - Third International Conference, MDA 2008, Proceedings

T2 - 3rd International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, MDA 2008

Y2 - 14 July 2008 through 14 July 2008

ER -