TY - GEN
T1 - Complex resonant recognition model in analysing Influenza A virus subtype protein sequences
AU - Chrysostomou, Charalambos
AU - Seker, Huseyin
AU - Aydin, Nizamettin
AU - Haris, Parvez I.
PY - 2010
Y1 - 2010
N2 - Resonant Recognition Method that uses discrete Fourier transform (DFT) and Electron-ion interaction potential amino acid scale (EIIP) is one of the techniques widely used for the analysis of protein sequences. However, DFT that generates complex output (imaginary and real frequency spectra) has shown to produce complementary information in other areas (e.g., ultrasound) were not taken into consideration. Therefore, for the first time, this study is concerned with the development of complex resonant recognition method (CRRM) for the analysis of groups of proteins using their sequence information. As a case study, the method developed is applied to extract characteristic frequency peaks of Influenza A subtypes Neuraminidase gene, for which Influenza A virus subtypes HINI, H2N2, H3N2 and H5NI proteins were extracted from Influenza Virus Resource database. The relationships of Influenza A subtypes that appear in CRRM real and imaginary spectra are found to be consistent to the biological link whereas this was not observed in the traditional RRM. H3N2 inherited NA gene from H2N2 and they are found to share the same characteristic frequency as seen in the real spectrum. In addition, HINI supplied the NA gene to H5NI and they also have the same characteristic frequency in the imaginary spectrum. The results clearly show that imaginary part of the CRRM clearly identified similarities and differences between the influenza sub-types at the proteomic level where real part and absolute value of the DFT were incapable of doing so. The results obtained for this study therefore suggest that the CRRM can not only produce additional biological information but also helps better distinguish biological differences between the families of the proteins. This is hence expected to help better understand mechanisms of the diseases and aid drug/vaccine development.
AB - Resonant Recognition Method that uses discrete Fourier transform (DFT) and Electron-ion interaction potential amino acid scale (EIIP) is one of the techniques widely used for the analysis of protein sequences. However, DFT that generates complex output (imaginary and real frequency spectra) has shown to produce complementary information in other areas (e.g., ultrasound) were not taken into consideration. Therefore, for the first time, this study is concerned with the development of complex resonant recognition method (CRRM) for the analysis of groups of proteins using their sequence information. As a case study, the method developed is applied to extract characteristic frequency peaks of Influenza A subtypes Neuraminidase gene, for which Influenza A virus subtypes HINI, H2N2, H3N2 and H5NI proteins were extracted from Influenza Virus Resource database. The relationships of Influenza A subtypes that appear in CRRM real and imaginary spectra are found to be consistent to the biological link whereas this was not observed in the traditional RRM. H3N2 inherited NA gene from H2N2 and they are found to share the same characteristic frequency as seen in the real spectrum. In addition, HINI supplied the NA gene to H5NI and they also have the same characteristic frequency in the imaginary spectrum. The results clearly show that imaginary part of the CRRM clearly identified similarities and differences between the influenza sub-types at the proteomic level where real part and absolute value of the DFT were incapable of doing so. The results obtained for this study therefore suggest that the CRRM can not only produce additional biological information but also helps better distinguish biological differences between the families of the proteins. This is hence expected to help better understand mechanisms of the diseases and aid drug/vaccine development.
KW - Complex resonant recognition model
KW - Discrete fourier transform
KW - Influenza a virus
KW - Neuraminidase
UR - http://www.scopus.com/inward/record.url?scp=79951634171&partnerID=8YFLogxK
U2 - 10.1109/ITAB.2010.5687621
DO - 10.1109/ITAB.2010.5687621
M3 - Conference contribution
AN - SCOPUS:79951634171
SN - 9781424465606
T3 - Proceedings of the IEEE/EMBS Region 8 International Conference on Information Technology Applications in Biomedicine, ITAB
BT - ITAB 2010 - 10th International Conference on Information Technology and Applications in Biomedicine
T2 - 10th International Conference on Information Technology and Applications in Biomedicine: Emerging Technologies for Patient Specific Healthcare, ITAB 2010
Y2 - 2 November 2010 through 5 November 2010
ER -