MS Thesis

• Aygün, E.; Oommen B.J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, 2010, 43, 3891

• Aygün, E.; Oommen B.J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, 2010, 43, 3891

My MS thesis was a research on protein function prediction. As a part of this work, I measured the contribution of the secondary structure information on the performance of protein function prediction and I applied Oommen-Kashyap syntactic transition probability calculation on the peptide classification problem. This is the first published work, as far as I know, that combines Oommen-Kashyap method and biological sequence analysis.

• Aygün, E.; Oommen B.J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, kabul edildi
• Aygün, E.; Oommen B.J. & Cataltepe, Z. On Utilizing Optimal and Information Theoretic Syntactic Modelling for Peptide Classification Pattern Recognition in Bioinformatics, 2009 (Sunum)

• Aygün, E.; Oommen B.J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, accepted
• Aygün, E.; Oommen B.J. & Cataltepe, Z. On Utilizing Optimal and Information Theoretic Syntactic Modelling for Peptide Classification Pattern Recognition in Bioinformatics, 2009 (Presentation)

• Aygün, E.; Oommen B. J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, accepted

• Aygün, E.; Oommen B. J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, kabul edildi

My MS thesis was a research on protein function prediction. As a part of this work, I measured the contribution of the secondary structure information on the performance of protein function prediction and I applied Oommen-Kashyap syntactic transition probability calculation on the peptide classification problem. This is the first published work, as far as I know, that incorporates Oommen-Kashyap method and biological sequence analysis.

My MS thesis was a research on protein function prediction. As a part of this work, I measured the contribution of the secondary structure information on the performance of protein function prediction and I applied Oommen-Kashyap transition probability calculation on the peptide classification problem. This is the first published work, as far as I know, that incorporates Oommen-Kashyap method and biological sequence analysis.

Thesis (in Turkish): Aygun2009.pdf

• Aygün, E.; Oommen B. J. & Cataltepe, Z. On Utilizing Optimal and Information Theoretic Syntactic Modelling for Peptide Classification Pattern Recognition in Bioinformatics, 2009 (Presentation)

Abstract:

• Aygün, E.; Oommen B. J. & Cataltepe, Z. Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, waiting for publishing
• Aygün, E.; Oommen B. J. & Cataltepe, Z. On Utilizing Optimal and Information Theoretic Syntactic Modelling for Peptide Classification Pattern Recognition in Bioinformatics, 2009
• Aygün, E.; Komurlu, C.; Aydin, Z. & Cataltepe, Z. Protein Function Prediction with Amino Acid Sequence and Secondary Structure Alignment Scores International Symposium on Health Informatics and Bioinformatics, 2008
• Filiz, A.; Aygün, E.; Keskin, O. & Cataltepe, Z. Importance of Secondary Structure Elements for Prediction of GO Annotations International Symposium on Health Informatics and Bioinformatics, 2008
• Aygün E. & Cataltepe Z. Gene Ontology (GO) Molecular Function Prediction Based on Alignment Scores International Symposium on Health Informatics and Bioinformatics, 2007
• Cataltepe, Z.; Ayan, U. & Aygün, E. Protein Function Prediction Using Motifs, Sequence Features, Alignment Scores Research in Computational Molecular Biology, 2007
• Cataltepe, Z.; Aygün, E.; Filiz, A.; Keskin, O.; Komurlu, C. & Altunbasak, Y. Dimensionality Reduction for Protein Function Prediction Automated Function Prediction – Biosapiens Joint Special Interest Group Meeting at ISMB/ECCB, 2007

Thesis (in Turkish): Aygun2009.pdf

Related Publications

• Aygün, E.; Oommen B. J. & Cataltepe, Z.

Peptide Classification Using Optimal and Information Theoretic Syntactic Modelling Pattern Recognition, waiting for publishing

• Aygün, E.; Oommen B. J. & Cataltepe, Z.

On Utilizing Optimal and Information Theoretic Syntactic Modelling for Peptide Classification Pattern Recognition in Bioinformatics, 2009

• Aygün, E.; Komurlu, C.; Aydin, Z. & Cataltepe, Z.

Protein Function Prediction with Amino Acid Sequence and Secondary Structure Alignment Scores International Symposium on Health Informatics and Bioinformatics, 2008

• Filiz, A.; Aygün, E.; Keskin, O. & Cataltepe, Z.

Importance of Secondary Structure Elements for Prediction of GO Annotations International Symposium on Health Informatics and Bioinformatics, 2008

• Aygün E. & Cataltepe Z.

Gene Ontology (GO) Molecular Function Prediction Based on Alignment Scores International Symposium on Health Informatics and Bioinformatics, 2007

• Cataltepe, Z.; Ayan, U. & Aygün, E.

Protein Function Prediction Using Motifs, Sequence Features, Alignment Scores Research in Computational Molecular Biology, 2007

• Cataltepe, Z.; Aygün, E.; Filiz, A.; Keskin, O.; Komurlu, C. & Altunbasak, Y.

Dimensionality Reduction for Protein Function Prediction Automated Function Prediction – Biosapiens Joint Special Interest Group Meeting at ISMB/ECCB, 2007

My MS thesis was a research on protein function prediction. As a part of this work, I measured the contribution of the secondary structure information on the performance of protein function prediction and I applied Oommen-Kashyap transition probability calculation on the peptide classification problem. This is the first published work, as far as I know, that incorporates Oommen-Kashyap method and biological sequence analysis.

Improvement of Protein Function Prediction Using Structural Information and Peptide Classification Using Syntactic Transition Probabilities

My MS thesis was a research on protein function prediction. As a part of this work, I measured the contribution of the secondary structure information on the performance of protein function prediction and I applied Oommen-Kashyap transition probability calculation on the peptide classification problem. This is the first published work that incorporates Oommen-Kashyap method and biological sequence analysis, as far as I know.

IMPROVEMENT OF PROTEIN FUNCTION PREDICTION USING STRUCTURAL INFORMATION AND PEPTIDE CLASSIFICATION USING SYNTACTIC TRANSITION PROBABILITIES