@inproceedings{ad1213b9fed443b69f0e63844a3d67a2,
title = "Application of multivariate analysis and vibrational spectroscopy in classification of biological systems",
abstract = "Fourier Transform Infrared (FTIR) and Raman spectroscopies have emerged as powerful tools for chemical analysis. This is due to their ability to provide detailed information about the spatial distribution of chemical composition at the molecular level. A biological sample, i.e. bacteria or fungi, has a typical spectrum. This spectral fingerprint, characterizes the sample and can therefore be used for differentiating between biology samples which belong to different groups, i.e., several different isolates of a given fungi. When the spectral differences between the groups are minute, multivariate analysis should be used to provide a good differentiation. We hereby review several results which demonstrate the differentiation success obtained by combining spectroscopy measurements and multivariate analysis.",
keywords = "Machine learning, Vibrational spectroscopy, biological samples, multivariate analysis, supervised and unsupervised methods",
author = "A. Salman and E. Shufan and I. Lapidot and L. Tsror and L. Zeiri and Sahu, \{R. K.\} and R. Moreh and S. Mordechai and M. Huleihel",
note = "Publisher Copyright: {\textcopyright} 2015 AIP Publishing LLC.; International Conference of Computational Methods in Sciences and Engineering 2015, ICCMSE 2015 ; Conference date: 20-03-2015 Through 23-03-2015",
year = "2015",
month = dec,
day = "31",
doi = "10.1063/1.4938993",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Zacharoula Kalogiratou and Simos, \{Theodore E.\} and Theodore Monovasilis and Simos, \{Theodore E.\} and Simos, \{Theodore E.\}",
booktitle = "International Conference of Computational Methods in Sciences and Engineering 2015, ICCMSE 2015",
}