scholarly journals PhotochemCAD 3: Diverse Modules for Photophysical Calculations with Multiple Spectral Databases

2018 ◽  
Vol 94 (2) ◽  
pp. 277-289 ◽  
Author(s):  
Masahiko Taniguchi ◽  
Hai Du ◽  
Jonathan S. Lindsey
Keyword(s):  
Spectral Databases

scholarly journals Defining and using microbial spectral databases

2002 ◽  
Vol 13 (7) ◽  
pp. 875-887 ◽  
Author(s):  
Jon G. Wilkes ◽  
Katherine L. Glover ◽  
Manuel Holcomb ◽  
Fatemeh Rafii ◽  
Xiaoxi Cao ◽  
...  
Keyword(s):  
Spectral Databases

scholarly journals 2125. Staphylococcus Species Identification by Fourier Transform Infrared (FTIR) Spectroscopic Techniques: A Cross-Lab Study

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S720-S720
Author(s):  
Tamao Tsutsumi ◽  
Alok Shah ◽  
Lisa M T Lam ◽  
Sanmarie Schlebusch ◽  
Annika Krueger ◽  
...  
Keyword(s):  
Fourier Transform ◽  
16S Rrna ◽  
Ftir Spectroscopy ◽  
Species Identification ◽  
Ftir Spectra ◽  
16S Rrna Sequencing ◽  
Spectroscopic Techniques ◽  
Rrna Sequencing ◽  
Perilesional Skin ◽  
Spectral Databases

Abstract Background Staphylococcus aureus is well known to be associated with atopic dermatitis. Recent studies also report S. aureus presence in lesional skin of squamous cell carcinoma (SCC) and its precursor lesion, actinic keratosis (AK). Therefore, it is of potential clinical interest to monitor skin S. aureus colonization on AK lesions. Fourier transform infrared (FTIR) spectroscopy is a cost-effective, nondestructive, and reagent-free technique for rapid microbial identification. It is based on the use of spectral databases developed with well-characterized strains in conjunction with the application of multivariate statistical analysis to elaborate classification models. In the present cross-lab study, spectral databases containing FTIR spectra of over 1000 staphylococcal isolates obtained from reference and clinical microbiology laboratories across Canada were employed in the FTIR spectroscopic identification of Staphylococcus spp. isolated from AK, SCC and perilesional skin of patients at the Princess Alexandra Hospital Dermatology Clinic in Brisbane, Australia. Methods FTIR spectra of 51 staphylococcal isolates from AK, SCC and perilesional skin were acquired by both attenuated total reflectance (ATR)-FTIR and transflection-FTIR spectroscopy. All isolates had been previously characterized by 16S rRNA sequencing. ATR- and transflection-FTIR spectra were recorded in triplicate from isolated colonies taken from the same agar plate. Identification of the bacteria was based on the similarities of their spectra with those in ATR- and transflection-FTIR spectral databases originating from the Canadian lab. Results Among the 51 staphylococcal isolates included in this study, identification of S. aureus (n = 24) with 100% specificity and 100% sensitivity was achieved by both ATR- and transflection-FTIR spectroscopy. Overall, FTIR-based species identification was in 90.2% concordance with 16S rRNA sequencing. Conclusion This cross-lab study demonstrates the applicability of Canadian isolate-based ATR- and transflection-FTIR spectral databases for the identification of clinical staphylococcal isolates obtained in Australia. The results support the potential utility of FTIR spectroscopic techniques to monitor skin S. aureus colonization on AK lesions. Disclosures All authors: No reported disclosures.

Reducing the Dimensionality of Plant Spectral Databases

2004 ◽  
Vol 42 (3) ◽  
pp. 570-576 ◽  
Author(s):  
I.E. Bell ◽  
G.V.G. Baranoski
Keyword(s):  
Spectral Databases

Estimating the degree of similarity overlap for structural data in spectral databases

2005 ◽  
Vol 543 (1-2) ◽  
pp. 177-180 ◽  
Author(s):  
T.A. Kornakova ◽  
T.F. Bogdanova ◽  
B.G. Derendyaev ◽  
V.N. Piottukh-Peletsky
Keyword(s):  
Structural Data ◽  
Degree Of Similarity ◽  
Spectral Databases

Soil Spectral Databases

2021 ◽  
Vol 76 (2) ◽  
pp. 54-59
Author(s):  
N. P. Kirillova ◽  
D. M. Khomiakov ◽  
E. I. Karavanova ◽  
D. A. Azikov ◽  
D. A. Zhulidova
Keyword(s):  
Spectral Databases

scholarly journals Mass spectral databases for LC/MS- and GC/MS-based metabolomics: State of the field and future prospects

2016 ◽  
Vol 78 ◽  
pp. 23-35 ◽  
Author(s):  
Maria Vinaixa ◽  
Emma L. Schymanski ◽  
Steffen Neumann ◽  
Miriam Navarro ◽  
Reza M. Salek ◽  
...  
Keyword(s):  
Future Prospects ◽  
Mass Spectral ◽  
Spectral Databases ◽  
State Of The Field
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