Full-length HPLC signal clustering and biomarker identification in tomato plants

M. Strickert; T. Czauderna; S. Peterek; A. Matros; H. P. Mock; U. Seiffert

doi:10.1142/9789812774118_0078

Full-length HPLC signal clustering and biomarker identification in tomato plants

M. Strickert, T. Czauderna, S. Peterek, A. Matros, H. P. Mock, U. Seiffert

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

2 Citations (Scopus)

Abstract

High resolution HPLC data of a tomato germ plasm collection are studied: Analysis of the molecular constituents of tomato peels from 55 experiments is conducted with focus on the visualization of the plant interrelationships, and on biomarker extraction for the identification of new and highly abundant substances at a wavelength of 280nm. 3000-dimensional chromatogram vectors are processed by state of-the-art and novel methods for baseline correction, data alignment, biomarker retrieval, and data clustering. These processing methods are applied to the tomato data set and the results are presented in a comparative manner, thereby focusing on interesting clusters and retention times of nutritionally valuable tomato lines.

Original language	English
Title of host publication	Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006
Publisher	World Scientific Publishing
Pages	549-556
Number of pages	8
ISBN (Electronic)	9812566902, 9789812566904
DOIs	https://doi.org/10.1142/9789812774118_0078
Publication status	Published - 1 Jan 2006
Externally published	Yes
Event	Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006 - Genova, Italy Duration: 29 Aug 2006 → 31 Aug 2006

Conference

Conference	Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006
Country	Italy
City	Genova
Period	29/08/06 → 31/08/06

Access to Document

10.1142/9789812774118_0078

Link to publication in Scopus

Cite this

@inproceedings{3f57cbdff006484b8f614bd16246ef16,

title = "Full-length HPLC signal clustering and biomarker identification in tomato plants",

abstract = "High resolution HPLC data of a tomato germ plasm collection are studied: Analysis of the molecular constituents of tomato peels from 55 experiments is conducted with focus on the visualization of the plant interrelationships, and on biomarker extraction for the identification of new and highly abundant substances at a wavelength of 280nm. 3000-dimensional chromatogram vectors are processed by state of-the-art and novel methods for baseline correction, data alignment, biomarker retrieval, and data clustering. These processing methods are applied to the tomato data set and the results are presented in a comparative manner, thereby focusing on interesting clusters and retention times of nutritionally valuable tomato lines.",

author = "M. Strickert and T. Czauderna and S. Peterek and A. Matros and Mock, {H. P.} and U. Seiffert",

year = "2006",

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doi = "10.1142/9789812774118_0078",

language = "English",

pages = "549--556",

booktitle = "Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006",

publisher = "World Scientific Publishing",

address = "Singapore",

note = "Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006 ; Conference date: 29-08-2006 Through 31-08-2006",

}

Strickert, M, Czauderna, T, Peterek, S, Matros, A, Mock, HP & Seiffert, U 2006, Full-length HPLC signal clustering and biomarker identification in tomato plants. in Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006. World Scientific Publishing, pp. 549-556, Applied Artificial Intelligence - 7th International Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference, FLINS 2006, Genova, Italy, 29/08/06. https://doi.org/10.1142/9789812774118_0078

Full-length HPLC signal clustering and biomarker identification in tomato plants. / Strickert, M.; Czauderna, T.; Peterek, S.; Matros, A.; Mock, H. P.; Seiffert, U.

Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006. World Scientific Publishing, 2006. p. 549-556.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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T1 - Full-length HPLC signal clustering and biomarker identification in tomato plants

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AU - Mock, H. P.

AU - Seiffert, U.

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AB - High resolution HPLC data of a tomato germ plasm collection are studied: Analysis of the molecular constituents of tomato peels from 55 experiments is conducted with focus on the visualization of the plant interrelationships, and on biomarker extraction for the identification of new and highly abundant substances at a wavelength of 280nm. 3000-dimensional chromatogram vectors are processed by state of-the-art and novel methods for baseline correction, data alignment, biomarker retrieval, and data clustering. These processing methods are applied to the tomato data set and the results are presented in a comparative manner, thereby focusing on interesting clusters and retention times of nutritionally valuable tomato lines.

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