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Learning Causal Networks from Gene Expression Data. A Probabilistic Time Series Model for Gene Regulatory Relationships and Learning the Model from Gene Expression Data

Код 913533

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Аннотация к книге "Learning Causal Networks from Gene Expression Data. A Probabilistic Time Series Model for Gene Regulatory Relationships and Learning the Model from Gene Expression Data"

In this work we present a new model for identifying dependencies within a gene regulatory cycle. The model incorporates both probabilistic and temporal aspects, but is kept deliberately simple to make it amenable for learning from the gene expression data of microarray experiments. A key simplifying feature in our model is the use of a compression function for collapsing multiple causes of gene expression into a single cause. This allows us to introduce a learning algorithm which avoids the...

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Издательство: Книга по требованию
Дата выхода: июль 2011
ISBN: 978-3-6391-9779-2
Объём: 172 страниц
Масса: 282 г
Размеры(высота, ширина, толщина), см: 23 x 16 x 1

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