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» Time Series Prediction Based on Gene Expression Programming
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BMCBI
2007
173views more  BMCBI 2007»
14 years 9 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
GECCO
2004
Springer
138views Optimization» more  GECCO 2004»
15 years 2 months ago
Comparing Genetic Programming and Evolution Strategies on Inferring Gene Regulatory Networks
Abstract. In recent years several strategies for inferring gene regulatory networks from observed time series data of gene expression have been suggested based on Evolutionary Algo...
Felix Streichert, Hannes Planatscher, Christian Sp...
TCBB
2011
14 years 4 months ago
Learning Genetic Regulatory Network Connectivity from Time Series Data
Recent experimental advances facilitate the collection of time series data that indicate which genes in a cell are expressed. This paper proposes an efficient method to generate th...
Nathan A. Barker, Chris J. Myers, Hiroyuki Kuwahar...
BMCBI
2006
123views more  BMCBI 2006»
14 years 9 months ago
Permutation test for periodicity in short time series data
Background: Periodic processes, such as the circadian rhythm, are important factors modulating and coordinating transcription of genes governing key metabolic pathways. Theoretica...
Andrey A. Ptitsyn, Sanjin Zvonic, Jeffrey M. Gimbl...
ICIC
2009
Springer
14 years 7 months ago
Inference of Differential Equation Models by Multi Expression Programming for Gene Regulatory Networks
This paper presents an evolutionary method for identifying the gene regulatory network from the observed time series data of gene expression using a system of ordinary differential...
Bin Yang, Yuehui Chen, Qingfang Meng