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ECML
2001
Springer
15 years 1 months ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...
BMCBI
2008
108views more  BMCBI 2008»
14 years 9 months ago
An analysis of the positional distribution of DNA motifs in promoter regions and its biological relevance
Background: Motif finding algorithms have developed in their ability to use computationally efficient methods to detect patterns in biological sequences. However the posterior cla...
Ana C. Casimiro, Susana Vinga, Ana T. Freitas, Arl...
BMCBI
2007
104views more  BMCBI 2007»
14 years 9 months ago
Using contextual and lexical features to restructure and validate the classification of biomedical concepts
Background: Biomedical ontologies are critical for integration of data from diverse sources and for use by knowledge-based biomedical applications, especially natural language pro...
Jung-Wei Fan, Hua Xu, Carol Friedman
JACM
2007
132views more  JACM 2007»
14 years 9 months ago
Dynamic ordered sets with exponential search trees
We introduce exponential search trees as a novel technique for converting static polynomial space search structures for ordered sets into fully-dynamic linear space data structure...
Arne Andersson, Mikkel Thorup
BMCBI
2004
208views more  BMCBI 2004»
14 years 9 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein