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» Inferring gene regression networks with model trees
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CIARP
2009
Springer
14 years 3 months ago
Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach
Abstract. An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many appl...
Fabrício Martins Lopes, Evaldo A. de Olivei...
AAAI
2008
13 years 11 months ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
GECCO
2005
Springer
180views Optimization» more  GECCO 2005»
14 years 2 months ago
Inference of gene regulatory networks using s-system and differential evolution
In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
Nasimul Noman, Hitoshi Iba
ICML
2006
IEEE
14 years 9 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
IJCNN
2007
IEEE
14 years 2 months ago
Search Strategies Guided by the Evidence for the Selection of Basis Functions in Regression
— This work addresses the problem of selecting a subset of basis functions for a model linear in the parameters for regression tasks. Basis functions from a set of candidates are...
Ignacio Barrio, Enrique Romero, Lluís Belan...