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Hybrid DNA Sequence Similarity Scheme for Training Support Vector Machines * Mamoun Awad, and Latifur Khan
 

Summary: 1
Hybrid DNA Sequence Similarity Scheme for Training Support Vector Machines *
Mamoun Awad, and Latifur Khan
Department of Computer Science
University of Texas at Dallas
Richardson, Texas 75083, USA
[maa013600,lkhan]@utdallas.edu
Abstract
Similarity between two DNA sequences is based on alignment.
There are different approaches of alignments; each has its own
specialty of bearing different information on DNA sequence.
This paper presents a study on similarity kernels based on
different similarity schemes and proposes a hybrid one.
Similarity Kernel is required in order to represent the distance
or similarity between two DNA sequences. The different
schemes of alignments and the cost of computing them, make it
further more difficult to decide what scheme to use. In this
study we combine different similarity schemes; each scheme is
deduced based on alignment. We demonstrate that combining
different similarity scheme does in fact generalize well in

  

Source: Awad, Mamoun Adel - College of Information Technology, United Arab Emirates University

 

Collections: Computer Technologies and Information Sciences