Measuring similarity and improving stability in biomarker identification methods applied to Fourier-transform infrared (FTIR) spectroscopy

• Published in: Journal of biophotonics Vol. 7; no. 3-4; pp. 254 - 265
• Main Authors: Trevisan, Júlio, Park, Juhyun, Angelov, Plamen P., Ahmadzai, Abdullah A., Gajjar, Ketan, Scott, Andrew D., Carmichael, Paul L., Martin, Francis L.
• Format: Journal Article
• Language: English
• Published: Berlin WILEY-VCH Verlag 01.04.2014; WILEY‐VCH Verlag; Wiley Subscription Services, Inc
• Subjects: Algorithms; Animals; Biomarkers; Biomarkers - chemistry; biospectroscopy; Brain - metabolism; Brain Neoplasms - diagnosis; Brain Neoplasms - metabolism; Classification; computational framework; Cytology; data mining; Endometriosis - diagnosis; Endometriosis - metabolism; Female; Fourier transforms; Fourier-transform infrared spectroscopy; Histology; Humans; Infrared spectroscopy; Mesocricetus; Models, Statistical; Multivariate Analysis; Reproducibility of Results; Similarity; Spectroscopy; Spectroscopy, Fourier Transform Infrared - methods; Stability; statistical data analysis; validation studies; biospectroscopy; computational framework; biomarkers; data mining; Fourier-transform infrared spectroscopy; statistical data analysis; validation studies; classification

FTIR spectroscopy is a powerful diagnostic tool that can also derive biochemical signatures of a wide range of cellular materials, such as cytology, histology, live cells, and biofluids. However, while classification is a well‐established subject, biomarker identification lacks standards and validat...