Thesis Defense Announcement
To:  The George Mason University Community

Candidate: Daniel P. Veltri
Program: Master of Science in Bioinformatics & Computational Biology 

Date:   Wednesday March 27, 2013
Time:   2:00 p.m.
Place:  George Mason University    	 
	      Nguyen Engineering Building, Room 2901
	   Fairfax Campus

Thesis Chair: Dr. Amarda Shehu
Committee Members: Dr. Iosif Vaisman, Dr. Barney Bishop

Title: "Physicochemcial Feature Selection for Cathelicidin Antimicrobial Peptides"

Due to recent attention on antimicrobial peptides (AMPs) as targets for antibacterial
drug research, many machine learning methods are now turning their attention to AMP
recognition. Approaches that rely on whole-peptide properties for recognition are
challenged by the great sequence diversity among AMPs for effective feature construction. This
thesis proposes a novel and complementary method for feature construction which relies on
an extensive list of position-based amino acid physicochemical properties. These features
are shown effective in the context of classification by support vector machine (SVM), both
in comparison to related work in recognition of AMPs and in a novel study on the
cathelicidin family. A detailed analysis and careful construction of a decoy dataset allows for the
highlighting of antimicrobial activity-related features in cathelicidins. Special attention is
also given to residue positions involved with enzymatic cleavage. The method presented in
this thesis is a first step towards understanding what confers to cathelicidins their activity
at the physicochemical level and may prove useful for future AMP design efforts.