Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/36140
Title: CISAPS: Complex Informational Spectrum for the Analysis of Protein Sequences
Authors: Chrysostomou, Charalambos
Seker, H.
Aydin, N.
First Published: 2015
Publisher: Hindawi Publishing Corporation
Citation: Advances in Bioinformatics, Volume 2015 (2015), Article ID 909765
Abstract: Complex informational spectrum analysis for protein sequences (CISAPS) and its web-based server are developed and presented. As recent studies show, only the use of the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient. Therefore, CISAPS is developed to consider and provide results in three forms including absolute, real, and imaginary spectrum. Biologically related features to the analysis of influenza A subtypes as presented as a case study in this study can also appear individually either in the real or imaginary spectrum. As the results presented, protein classes can present similarities or differences according to the features extracted from CISAPS web server. These associations are probable to be related with the protein feature that the specific amino acid index represents. In addition, various technical issues such as zero-padding and windowing that may affect the analysis are also addressed. CISAPS uses an expanded list of 611 unique amino acid indices where each one represents a different property to perform the analysis. This web-based server enables researchers with little knowledge of signal processing methods to apply and include complex informational spectrum analysis to their work.
DOI Link: 10.1155/2015/909765
ISSN: 1687-8027
eISSN: 1687-8035
Links: http://www.hindawi.com/journals/abi/2015/909765
http://hdl.handle.net/2381/36140
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2015 Charalambos Chrysostomou et al. This is an open access article distributed under the Creative Commons Attribution License CC BY 3.0 http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Appears in Collections:Published Articles, Dept. of Genetics

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