Probabilistic graphical models for genetics, genomics, and postgenomics / edited by Christine Sinoquet and Raphael Mourad.
At the crossroads between statistics and machine learning, probabilistic graphical models (PGMs) provide a powerful formal framework to model complex data. An expanding volume of biological data of various types, the so-called 'omics', is in need of accurate and efficient methods for model...
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