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BMCBI
2010
170views more  BMCBI 2010»
13 years 8 months ago
Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...
Alex Aussem, André Tchernof, Sergio Rodrigu...
IJCNN
2006
IEEE
14 years 2 months ago
In-Place Learning for Positional and Scale Invariance
— In-place learning is a biologically inspired concept, meaning that the computational network is responsible for its own learning. With in-place learning, there is no need for a...
Juyang Weng, Hong Lu, Tianyu Luwang, Xiangyang Xue
CMSB
2004
Springer
14 years 1 months ago
Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods
In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble le...
Huma Lodhi, Stephen Muggleton
RECOMB
2003
Springer
14 years 8 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
ISMB
1994
13 years 10 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya