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CIBB
2008
15 years 6 months ago
Analysis of Kernel Based Protein Classification Strategies Using Pairwise Sequence Alignment Measures
Abstract. We evaluated methods of protein classification that use kernels built from BLAST output parameters. Protein sequences were represented as vectors of parameters (e.g. simi...
Dino Franklin, Somdutta Dhir, Sándor Pongor
CORR
2008
Springer
108views Education» more  CORR 2008»
15 years 4 months ago
Hierarchical Bag of Paths for Kernel Based Shape Classification
Graph kernels methods are based on an implicit embedding of graphs within a vector space of large dimension. This implicit embedding allows to apply to graphs methods which where u...
François-Xavier Dupé, Luc Brun
JMLR
2006
116views more  JMLR 2006»
15 years 4 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
PR
2006
110views more  PR 2006»
15 years 4 months ago
Classifying protein sequences using hydropathy blocks
The annotation of proteins can be achieved by classifying the protein of interest into a certain known protein family to induce its functional and structural features. This paper ...
De-Shuang Huang, Xing-Ming Zhao, Guang-Bin Huang, ...
TCBB
2008
138views more  TCBB 2008»
15 years 4 months ago
PairProSVM: Protein Subcellular Localization Based on Local Pairwise Profile Alignment and SVM
The subcellular locations of proteins are important functional annotations. An effective and reliable subcellular localization method is necessary for proteomics research. This pap...
Man-Wai Mak, Jian Guo, Sun-Yuan Kung