A hybrid least squares and principal component analysis algorithm for Raman spectroscopy

PLoS ONE

Volumn 7, Issue 6, 2012, Pages

  van de Sompel, Dominique ^a   Garai, Ellis ^a   Zavaleta, Cristina ^a   Gambhir, Sanjiv Sam ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GOLD NANOPARTICLE; SILICON DIOXIDE;

ALGORITHM; ARTICLE; COLON; CONTROLLED STUDY; HYBRID LEAST SQUARES; HYBRID LINEAR ANALYSIS; INTERMETHOD COMPARISON; PRINCIPAL COMPONENT ANALYSIS; RAMAN SPECTROMETRY; REGRESSION ANALYSIS; SIMULATION; SWINE;

ALGORITHMS; ANIMALS; COMPUTER SIMULATION; GOLD; LEAST-SQUARES ANALYSIS; NANOPARTICLES; PRINCIPAL COMPONENT ANALYSIS; SILICON DIOXIDE; SPECTRUM ANALYSIS, RAMAN;

EID: 84862490158     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0038850     Document Type: Article

References (14)

1. Zavaleta C, Smith B, Walton I, Doering W, Davis G, et al. (2009) Multiplexed imaging of surface enhanced Raman scattering nanotags in living mice using noninvasive Raman spectroscopy. Proceedings of the National Academy of Sciences 106: 13511.
2. Fortina P, Kricka L, Surrey S, Grodzinski P, (2005) Nanobiotechnology: the promise and reality of new approaches to molecular recognition. TRENDS in Biotechnology 23: 168-173.
3. Zavaleta C, Kircher M, Gambhir S, (2011) Raman's effect on molecular imaging. Journal of Nuclear Medicine 52: 1839-1844.
4. Lutz B, Dentinger C, Nguyen L, Sun L, Zhang J, et al. (2008) Spectral analysis of multiplex Raman probe signatures. ACS nano 2: 2306-2314.
5. Lieber C, Mahadevan-Jansen A, (2003) Automated method for subtraction of fluorescence from biological raman spectra. Applied Spectroscopy 57: 1363-1367.
6. Zhao J, Lui H, McLean D, Zeng H, (2007) Automated autofluorescence background subtraction algorithm for biomedical raman spectroscopy. Applied spectroscopy 61: 1225-1232.
7. Zhang Z, Chen S, Liang Y, (2010) Baseline correction using adaptive iteratively reweighted penalized least squares. Analyst 135: 1138-1146.
8. Kode K, Shachaf C, Elchuri S, Nolan G, Paik D, (2011) Raman labeled nanoparticles: characterization of variability and improved method for unmixing. Journal of Raman Spectroscopy In press.
9. Faber K, Kowalski B, (1997) Propagation of measurement errors for the validation of predictions obtained by principal component regression and partial least squares. Journal of chemometrics 11: 181-238.
10. Geladi P, Kowalski B, (1986) Partial least-squares regression: a tutorial. Analytica chimica acta 185: 1-17.
11. Haaland D, Thomas E, (1988) Partial least-squares methods for spectral analyses. 1. relation to other quantitative calibration methods and the extraction of qualitative information. Analytical Chemistry 60: 1193-1202.
12. Berger A, Koo T, Itzkan I, Feld M, (1998) An enhanced algorithm for linear multivariate calibration. Analytical chemistry 70: 623-627.
13. Keren S, Zavaleta C, Cheng Z, de La Zerda A, Gheysens O, et al. (2008) Noninvasive molecular imaging of small living subjects using raman spectroscopy. Proceedings of the National Academy of Sciences 105: 5844.
14. Abu-Hatab N, John J, Oran J, SepaniakM (2007) Multiplexed microfluidic surface-enhanced raman spectroscopy. Applied spectroscopy 61: 1116-1122.