352
acids with the most similar ones and try to fit the reconstructed spectrum for the
corresponding optimal subregions.
Another, still unexplored possibility, is to take into account the high energy region above 2500 cm
−1
. Figs. 12.1 and 12.2 clearly show significant spectral differences in this range. We plan to analyse this wavenumber interval using similarity
analysis techniques described in this work.
one should be rather cautious while trying to interpret the results of statistical
similarity analysis in terms of structural/chemical similarities. It should be mentioned, however, that the amino acids which exhibit largest statistical similarities
are also strongly chemically similar. this is nicely illustrated, e.g., by the neighbouring positions of valine, leucine and isoleucine in the similarity matrix shown
in Fig. 12.3.
Acknowledgements the research was supported by the European union within European
Regional development Fund, through grant Innovative Economy (PoIg.01.01.02-00-008/08).
References
1. Aroca R (2006) Surface-enhanced vibrational spectroscopy. Wiley, Chichester
2. Le Ru EC, Etchegoin Pg (2008) Principles of surface-enhanced Raman spectroscopy. Elsevier Science
3. Zhu g, Zhu X, Fan Q, Wan X (2011) Spectrochim Acta A 78:1187
4. Boldyreva E (2007) In: Boeyens JCA, ogilvie JF (eds) models, mysteries and magic of molecules. Springer. p 167
5. tanabe K, Saeki S (1975) Anal Chem 47:118
6. Li J, hibbert dB, Fuller S, vaughn g (2006) Chemometrics and intelligent laboratory systems
82:50
7. Culka A, Jehlicka J, Edwards hgm (2010) Spectrochim Acta A 77:978
8. destrade C, garrigou-Lagrange C, Forel mt (1971) J mol Struct 10:203
9. Stenback h (1976) J Raman Spectrosc 5:49
10. machida K, Kagayama A, Saito Y, Kuroda Y, uno t (1977) Spectrochim Acta A 33:569
11. Kakihana m, Akiyama m, Nagumo t, okamoto m (1988) Z Naturforsch A: Phys Sci 43:774
12. Stewart S, Fredericks Pm (1999) Spectrochim Acta A 55:1641
13. Kumar S, Rai AK, Singh vB, Rai SB (2005) Spectrochim Acta A 61:2741
14. murli C, thomas S, venkateswaran S, Sharma Sm (2005) Physica B 364:233
15. Fukushima K, onishi t, Shimanouchi t, mizushima S (1959) Spectrochim Acta 236
16. Wang Ch, Storms Rd (1971) J Chem Phys 55:3291
17. machida K, Kagayama A, Saito Y, uno t (1978) Spectrochim Acta A 34:909
18. Susi h, Byler dm (1980) J mol Struct 63:1
19. Forss S (1982) J Raman Spectrosc 12:266
20. migliori A, maxton Pm, Clogston Am, Zirngiebl E, Lowe m (1988) Phys Rev B: Condens
matter 38:13464
21. Kettle SFA, Lugwisha E, vorderwisch P, Eckert J (1990) Spectrochim Acta A 46:921
22. gong Y, Wang W-q (2006) guangpuxue Yu guangpu Fenxi 26:90
23. vijayan N, Rajasekaran S, Bhagavannarayana g, Babu RR, gopalakrishnan R, Palanichamy
m, Ramasamy P (2006) Cryst growth des 6:2441
24. gong Y, Zhao J, Chin BY, Wang W (2008) Proc China Assoc Sci technol 4:187
T. Roliński et al.
acids with the most similar ones and try to fit the reconstructed spectrum for the
corresponding optimal subregions.
Another, still unexplored possibility, is to take into account the high energy region above 2500 cm
−1
. Figs. 12.1 and 12.2 clearly show significant spectral differences in this range. We plan to analyse this wavenumber interval using similarity
analysis techniques described in this work.
one should be rather cautious while trying to interpret the results of statistical
similarity analysis in terms of structural/chemical similarities. It should be mentioned, however, that the amino acids which exhibit largest statistical similarities
are also strongly chemically similar. this is nicely illustrated, e.g., by the neighbouring positions of valine, leucine and isoleucine in the similarity matrix shown
in Fig. 12.3.
Acknowledgements the research was supported by the European union within European
Regional development Fund, through grant Innovative Economy (PoIg.01.01.02-00-008/08).
References
1. Aroca R (2006) Surface-enhanced vibrational spectroscopy. Wiley, Chichester
2. Le Ru EC, Etchegoin Pg (2008) Principles of surface-enhanced Raman spectroscopy. Elsevier Science
3. Zhu g, Zhu X, Fan Q, Wan X (2011) Spectrochim Acta A 78:1187
4. Boldyreva E (2007) In: Boeyens JCA, ogilvie JF (eds) models, mysteries and magic of molecules. Springer. p 167
5. tanabe K, Saeki S (1975) Anal Chem 47:118
6. Li J, hibbert dB, Fuller S, vaughn g (2006) Chemometrics and intelligent laboratory systems
82:50
7. Culka A, Jehlicka J, Edwards hgm (2010) Spectrochim Acta A 77:978
8. destrade C, garrigou-Lagrange C, Forel mt (1971) J mol Struct 10:203
9. Stenback h (1976) J Raman Spectrosc 5:49
10. machida K, Kagayama A, Saito Y, Kuroda Y, uno t (1977) Spectrochim Acta A 33:569
11. Kakihana m, Akiyama m, Nagumo t, okamoto m (1988) Z Naturforsch A: Phys Sci 43:774
12. Stewart S, Fredericks Pm (1999) Spectrochim Acta A 55:1641
13. Kumar S, Rai AK, Singh vB, Rai SB (2005) Spectrochim Acta A 61:2741
14. murli C, thomas S, venkateswaran S, Sharma Sm (2005) Physica B 364:233
15. Fukushima K, onishi t, Shimanouchi t, mizushima S (1959) Spectrochim Acta 236
16. Wang Ch, Storms Rd (1971) J Chem Phys 55:3291
17. machida K, Kagayama A, Saito Y, uno t (1978) Spectrochim Acta A 34:909
18. Susi h, Byler dm (1980) J mol Struct 63:1
19. Forss S (1982) J Raman Spectrosc 12:266
20. migliori A, maxton Pm, Clogston Am, Zirngiebl E, Lowe m (1988) Phys Rev B: Condens
matter 38:13464
21. Kettle SFA, Lugwisha E, vorderwisch P, Eckert J (1990) Spectrochim Acta A 46:921
22. gong Y, Wang W-q (2006) guangpuxue Yu guangpu Fenxi 26:90
23. vijayan N, Rajasekaran S, Bhagavannarayana g, Babu RR, gopalakrishnan R, Palanichamy
m, Ramasamy P (2006) Cryst growth des 6:2441
24. gong Y, Zhao J, Chin BY, Wang W (2008) Proc China Assoc Sci technol 4:187
T. Roliński et al.