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CVPR
1999
IEEE
14 years 9 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...
BMCBI
2007
215views more  BMCBI 2007»
13 years 7 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
BMCBI
2006
126views more  BMCBI 2006»
13 years 7 months ago
A joint model of regulatory and metabolic networks
Background: Gene regulation and metabolic reactions are two primary activities of life. Although many works have been dedicated to study each system, the coupling between them is ...
Chen-Hsiang Yeang, Martin Vingron
RECOMB
2005
Springer
14 years 7 months ago
Combinatorial Genetic Regulatory Network Analysis Tools for High Throughput Transcriptomic Data
: A series of genome-scale algorithms and high-performance implementations is described and shown to be useful in the genetic analysis of gene transcription. With them it is possib...
Elissa J. Chesler, Michael A. Langston