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» Predicting Nucleolar Proteins Using Support-Vector Machines
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KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 7 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
ECAI
2004
Springer
14 years 23 days ago
A Generalized Quadratic Loss for Support Vector Machines
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Filippo Portera, Alessandro Sperduti
BMCBI
2007
142views more  BMCBI 2007»
13 years 7 months ago
Predicting and improving the protein sequence alignment quality by support vector regression
Background: For successful protein structure prediction by comparative modeling, in addition to identifying a good template protein with known structure, obtaining an accurate seq...
Minho Lee, Chan-seok Jeong, Dongsup Kim
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
13 years 12 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
BMCBI
2011
13 years 2 months ago
NClassG+: A classifier for non-classically secreted Gram-positive bacterial proteins
Background: Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two met...
Daniel Restrepo-Montoya, Camilo Pino, Luis F. Ni&n...