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» Causal inference using the algorithmic Markov condition
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JMLR
2010
82views more  JMLR 2010»
14 years 4 months ago
TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries
We present an artificially simulated dataset (TIED) constructed so that there are many minimal sets of variables with maximal predictivity (i.e., Markov boundaries) and likewise m...
Alexander R. Statnikov, Constantin F. Aliferis
BMCBI
2005
189views more  BMCBI 2005»
14 years 9 months ago
Quantitative inference of dynamic regulatory pathways via microarray data
Background: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway ar...
Wen-Chieh Chang, Chang-Wei Li, Bor-Sen Chen
APIN
2004
107views more  APIN 2004»
14 years 9 months ago
Designing Polymer Blends Using Neural Networks, Genetic Algorithms, and Markov Chains
In this paper we present a new technique to simulate polymer blends that overcomes the shortcomings in polymer system modeling. This method has an inherent advantage in that the v...
N. K. Roy, Walter D. Potter, D. P. Landau
NAR
2010
123views more  NAR 2010»
14 years 4 months ago
Discovering causal signaling pathways through gene-expression patterns
High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant members...
Jignesh R. Parikh, Bertram Klinger, Yu Xia, Jarrod...
UAI
2004
14 years 11 months ago
Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences
We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of s...
Cosma Rohilla Shalizi, Kristina Lisa Shalizi