GAEM: Genetic Algorithm based Expectation-Maximization for inferring Gene Regulatory Networks from incomplete data

In Bioinformatics, inferring the structure of a Gene Regulatory Network (GRN) from incomplete gene expression data is a difficult task. One popular method for inferring the structure GRNs is to apply the Path Consistency Algorithm based on Conditional Mutual Information (PCA-CMI). Although PCA-CMI e...

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Vydané v:	Computers in biology and medicine Ročník 183; s. 109238
Hlavní autori:	Niloofar, Parisa, Aghdam, Rosa, Eslahchi, Changiz
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Ltd 01.12.2024 Elsevier Limited
Predmet:	Algorithms Bayesian network Bioinformatics Computational Biology - methods Conditional Mutual Information Convergence Databases, Genetic Datasets Expectation-Maximization Gene expression Gene Expression Profiling - methods Gene Regulatory Network Gene Regulatory Networks - genetics Genetic algorithm Genetic algorithms Humans Internal Medicine Machine learning Maximization Missing values Models, Genetic Optimization Other Conditional Mutual Information Gene Regulatory Network Genetic algorithm Bayesian network Expectation-Maximization Missing values
ISSN:	0010-4825, 1879-0534, 1879-0534
On-line prístup:	Získať plný text
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