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ISNN
2011
Springer
14 years 9 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
BMCBI
2008
122views more  BMCBI 2008»
15 years 6 months ago
Generating samples for association studies based on HapMap data
Background: With the completion of the HapMap project, a variety of computational algorithms and tools have been proposed for haplotype inference, tag SNP selection and genome-wid...
Jing Li, Yixuan Chen
BMCBI
2006
126views more  BMCBI 2006»
15 years 6 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo
BMCBI
2010
118views more  BMCBI 2010»
15 years 6 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
RECOMB
2003
Springer
16 years 7 months ago
Physical network models and multi-source data integration
We develop a new framework for inferring models of transcriptional regulation. The models in this approach, which we call physical models, are constructed on the basis of verifiab...
Chen-Hsiang Yeang, Tommi Jaakkola