Spectral analysis of protein sequences
2006 (English)In: Advances in Machine Learning and Cybernetics: 4th International Conference, ICMLC 2005, Guangzhou, China, August 18-21, 2005, Revised Selected Papers / [ed] Daniel S. Yeung, Zhi-Qiang Liu, Xi-Zhao Wang and Hong Yan, Springer Berlin/Heidelberg, 2006, 595-604 p.Chapter in book (Other academic)Text
Analysis of protein sequences can avoid many problems inherently existing in the study of nucleotide sequences given the knowledge that DNA sequences contain all the information for regulating protein expression. This paper presents a spectral approach for calculating the similarity of protein sequences, which can be useful for the inferences of protein functions. The proposed method is based on the mathematical concepts of linear predictive coding and cepstral distortion measure. We show that this spectral approach can reveal non-trivial results from an experimental study of a set of functionally related and functionally non-related protein sequences, and has advantages over some existing approaches.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2006. 595-604 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3930
IdentifiersURN: urn:nbn:se:liu:diva-125010DOI: 10.1007/11739685_62ISBN: 978-3-540-33584-9 (Print)ISBN: 978-3-540-33585-6 (Online)OAI: oai:DiVA.org:liu-125010DiVA: diva2:902789