Probabilistic graphical models are among the leading methodologies to handle complex stochasting systems. Recently, several proposal have been performed to properly handle causal information. These generalizations make possible to build genetic networks where both causal information and stocastic association are present.
Bioinformatics and Statistics / F. M. Stefanini. - ELETTRONICO. - (2005), pp. 1-30. (Intervento presentato al convegno European Conference EACDA 2005 tenutosi a Pisa nel Settembre 2005).
Bioinformatics and Statistics
STEFANINI, FEDERICO MATTIA
2005
Abstract
Probabilistic graphical models are among the leading methodologies to handle complex stochasting systems. Recently, several proposal have been performed to properly handle causal information. These generalizations make possible to build genetic networks where both causal information and stocastic association are present.
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