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» Predicting Nucleolar Proteins Using Support-Vector Machines
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138
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BMCBI
2004
123views more  BMCBI 2004»
15 years 3 months ago
Interaction profile-based protein classification of death domain
Background: The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experim...
Drew Lett, Michael Hsing, Frederic Pio
122
Voted
BMCBI
2007
121views more  BMCBI 2007»
15 years 3 months ago
Predicting zinc binding at the proteome level
Background: Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for ...
Andrea Passerini, Claudia Andreini, Sauro Menchett...
147
Voted
RECOMB
2004
Springer
16 years 4 months ago
A class of edit kernels for SVMs to predict translation initiation sites in eukaryotic mRNAs
The prediction of translation initiation sites (TISs) in eukaryotic mRNAs has been a challenging problem in computational molecular biology. In this paper, we present a new algori...
Haifeng Li, Tao Jiang
148
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ALT
2000
Springer
15 years 7 months ago
Computationally Efficient Transductive Machines
In this paper1 we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector mac...
Craig Saunders, Alexander Gammerman, Volodya Vovk
129
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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 4 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil