Characterisation and Classification of Protein Sequences by Using Enhanced Amino Acid Indices ...

328 Pages·2009·21.2 MB·English

Characterisation and Classification of
Protein Sequences by Using Enhanced
Amino Acid Indices and Signal
Processing-Based Methods
Charalambos Chrysostomou
Faculty of Technology
De Montfort University
A thesis submitted for the degree of
Doctor of Philosophy
May 2013

Iwouldliketodedicatethisthesistomyfamily,fortheirsupportthroughout
thecourseofthisthesis.

Acknowledgements
The author wishes to express his gratitude to his first supervisor, Dr Huseyin
Seker, who was abundantly helpful and offered invaluable assistance, support
and guidance. Deepest gratitudes are also due to the members of the supervi-
sorycommittee,DrRutaFurmonaviciene,andProfessorRobertJohn,without
whose knowledge and assistance this study would not have been successful.
The author would also like to thank his family for the support and encourage-
ment they provided through the years. In conclusion, the author recognises
that this research project would not have been possible without the financial
assistanceofDeMontfortUniversity,whichfullyfundedthisproject.

Declaration
I declare that the work described in my thesis is original work undertaken by
me for the degree of Doctor of Philosophy, at The Centre for Computational
Intelligence (CCI), at De Montfort University, United Kingdom. No part of
the material described in this thesis has been submitted for the award of any
otherdegreeorqualification.

Publications Produced From The Ph.D. Thesis
PublishedPapers
1. C. Chrysostomou, H. Seker, N. Aydin, and P. Haris, “Complex reso-
nant recognition model in analysing influenza a virus subtype protein
sequences,” in Proceedings of the 10th IEEE International Conference
on Information Technology and Applications in Biomedicine, (Corfu,
Greece),pp. 1-4,November2010.
C.Chrysostomoudevelopedthemethodology,collectedandanalysedthe
data,evaluatedtheresultsproducedandwrotethepaper.
2. C. Chrysostomou, H. Seker, and N. Aydin, “Effects of windowing and
zero-paddingoncomplexresonantrecognitionmodelforproteinsequence
analysis,”inProceedingsofthe33rdAnnualInternationalConferenceof
the IEEE Engineering in Medicine and Biology Society, (Boston, USA),
pp. 4955-8,August2011.
C.Chrysostomoudevelopedthemethodology,collectedandanalysedthe
data,evaluatedtheresultsproducedandwrotethepaper.
3. C.Chrysostomou,H.Seker,andN.Aydin,“Investigationintotheeffects
of an individual amino acid on protein function by means of a resonant
recognition model,” in Proceedings of the 5th International Conference
on Convergence and Hybrid Information Technology, (Korea), pp. 229-
236,Springer-Verlag,2011.
C.Chrysostomoudevelopedthemethodology,collectedandanalysedthe
data,evaluatedtheresultsproducedandwrotethepaper.
4. C. Chrysostomou and H. Seker, “Construction of Protein Distance Ma-
trix Based on Discrete Fourier Transform”, in Proceedings of the 35rd
Annual International Conference of the IEEE Engineering in Medicine
andBiologySociety,(Osaka,Japan),July2013
C.Chrysostomoudevelopedthemethodology,collectedandanalysedthe
data,evaluatedtheresultsproducedandwrotethepaper.
5. C. Chrysostomou and H. Seker, “Signal-processing based bioinformat-
ics approach for Classification of Protein Sequences”, in Proceedings of
the 35rd Annual International Conference of the IEEE Engineering in
MedicineandBiologySociety,(Osaka,Japan),July2013
C.Chrysostomoudevelopedthemethodology,collectedandanalysedthe
data,evaluatedtheresultsproducedandwrotethepaper.
6. C.J. Carmona, C. Chrysostomou, H. Seker, M.J. del Jesus. Fuzzy Rules
forDescribingSubgroupsfromInfluenzaAVirusUsingaMulti-objective
EvolutionaryAlgorithm. AppliedSoftComputing(2013)
C. Chrysostomou collected the data used in the analysis, evaluate the
resultsproducedandwrotepartofthepaper.