TY - GEN
T1 - Features extraction using free score of words for classifying conotoxin superfamily
AU - Zaki, Nazar
AU - Campbell, Piers
AU - Wolfsheimer, Stefan
AU - Nuel, Gregory
PY - 2011
Y1 - 2011
N2 - Interest in Conotoxin has been rapidly growing over the past number of years due to its potential for effective use in the design of drugs to treat a myriad of conditions including, neuromuscular disorders, chronic pain and schizophrenia. As a result it is necessary to develop powerful and efficient techniques which can accurately classify conotoxin super families. In this paper, we propose a novel technique which makes use of support vector machines for classification. The method which considers suboptimal alignments of words with restricted length and computes local alignment partition functions to produce free scores for the alignments plays the key role in the feature extraction step of support vector machine classification. In the classification of conotoxin proteins, the proposed approach, SVM-Freescore, demonstrates its potential use by yielding an improved sensitivity and specificity of approximately 5.864% and 3.76%, respectively.
AB - Interest in Conotoxin has been rapidly growing over the past number of years due to its potential for effective use in the design of drugs to treat a myriad of conditions including, neuromuscular disorders, chronic pain and schizophrenia. As a result it is necessary to develop powerful and efficient techniques which can accurately classify conotoxin super families. In this paper, we propose a novel technique which makes use of support vector machines for classification. The method which considers suboptimal alignments of words with restricted length and computes local alignment partition functions to produce free scores for the alignments plays the key role in the feature extraction step of support vector machine classification. In the classification of conotoxin proteins, the proposed approach, SVM-Freescore, demonstrates its potential use by yielding an improved sensitivity and specificity of approximately 5.864% and 3.76%, respectively.
KW - Conotoxin
KW - free-scores
KW - local alignment
KW - suboptimal alignments
KW - support vector machines
UR - http://www.scopus.com/inward/record.url?scp=81255150763&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=81255150763&partnerID=8YFLogxK
U2 - 10.1109/SNPD.2011.34
DO - 10.1109/SNPD.2011.34
M3 - Conference contribution
AN - SCOPUS:81255150763
SN - 9780769544755
T3 - Proceedings - 2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing, SNPD 2011
SP - 79
EP - 84
BT - Proceedings - 2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing, SNPD 2011
T2 - 2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing, SNPD 2011
Y2 - 6 July 2011 through 8 July 2011
ER -