Artificial Neural Networks for Classification in Metabolomic Studies of Whole Cells Using H-1 Nuclear Magnetic Resonance

Varování

Publikace nespadá pod Ústav výpočetní techniky, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.

Autoři	BROUGHAM D F IVANOVA G. GOTTSCHALK M. COLLINS D M EUSTACE A J O CONNOR R. HAVEL Josef
Rok publikování	2011
Druh	Článek v odborném periodiku
Časopis / Zdroj	Journal of Biomedicine and Biotechnology
Fakulta / Pracoviště MU	Přírodovědecká fakulta
Citace
Doi	http://dx.doi.org/10.1155/2011/158094
Obor	Analytická chemie, separace
Klíčová slova	NMR SPECTROSCOPIC DATA; HUMAN BRAIN-TUMORS; H-1-NMR SPECTROSCOPY; PATTERN-RECOGNITION; IN-VITRO; EXTRACTS; IDENTIFICATION; LINES; VIVO; RESISTANCE
Popis	We report the successful classification, by artificial neural networks (ANNs), of H-1 NMR spectroscopic data recorded on whole-cell culture samples of four different lung carcinoma cell lines, which display different drug resistance patterns. The robustness of the approach was demonstrated by its ability to classify the cell line correctly in 100% of cases, despite the demonstrated presence of operator-induced sources of variation, and irrespective of which spectra are used for training and for validation. The study demonstrates the potential of ANN for lung carcinoma classification in realistic situations.
Související projekty:	Centrum biofyzikální chemie, bioelektrochemie a bioanalýzy. Nové nástroje pro genomiku, proteomiku a biomedicínu