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» On Sequence Prediction for Arbitrary Measures
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SAC
2005
ACM
14 years 1 months ago
Comparing approaches to predict transmembrane domains in protein sequences
There are today several systems for predicting transmembrane domains in membrane protein sequences. As they are based on different classifiers as well as different pre- and post-p...
Paul Davidsson, Johan Hagelbäck, Kenny Svenss...
CIBCB
2007
IEEE
14 years 1 months ago
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins
Abstract— We applied Support Vector Machines to the prediction of the subcellular localization of transmembrane proteins, and compared the performance of different sequence kerne...
Stefan Maetschke, Marcus Gallagher, Mikael Bod&eac...
ICML
2004
IEEE
14 years 29 days ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
BMCBI
2010
117views more  BMCBI 2010»
13 years 7 months ago
New decoding algorithms for Hidden Markov Models using distance measures on labellings
Background: Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. Results: We give a set of algorithms to com...
Daniel G. Brown 0001, Jakub Truszkowski
ICMLA
2007
13 years 9 months ago
Machine learned regression for abductive DNA sequencing
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
David Thornley, Maxim Zverev, Stavros Petridis