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 | |
| 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 |
Cite this
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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
TY - GEN
T1 - Full-length HPLC signal clustering and biomarker identification in tomato plants
AU - Strickert, M.
AU - Czauderna, T.
AU - Peterek, S.
AU - Matros, A.
AU - Mock, H. P.
AU - Seiffert, U.
PY - 2006/1/1
Y1 - 2006/1/1
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=85036478990&partnerID=8YFLogxK
U2 - 10.1142/9789812774118_0078
DO - 10.1142/9789812774118_0078
M3 - Conference Paper
SP - 549
EP - 556
BT - Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006
PB - World Scientific Publishing
ER -