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» Learning Markov Logic Networks Using Structural Motifs
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AAAI
2010
13 years 6 months ago
Structure Learning for Markov Logic Networks with Many Descriptive Attributes
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyua...
BMCBI
2006
116views more  BMCBI 2006»
13 years 5 months ago
Optimized mixed Markov models for motif identification
Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...
BMCBI
2007
141views more  BMCBI 2007»
13 years 5 months ago
Using structural motif descriptors for sequence-based binding site prediction
Background: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, ...
Andreas Henschel, Christof Winter, Wan Kyu Kim, Mi...
BMCBI
2004
177views more  BMCBI 2004»
13 years 4 months ago
Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model
Background: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservati...
Andrew F. Neuwald, Jun S. Liu
AAAI
2007
13 years 7 months ago
Mapping and Revising Markov Logic Networks for Transfer Learning
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Moon...