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Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics Christine Sinoquet
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Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics
Christine Sinoquet
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 modelling and PGMs are expected to have a prominent role to play.
480 pages, 99 b/w and 10 colour illustrations
| Medios de comunicación | Libros Hardcover Book (Libro con lomo y cubierta duros) |
| Publicado | 25 de noviembre de 2014 |
| ISBN13 | 9780198709022 |
| Editores | Oxford University Press |
| Páginas | 478 |
| Dimensiones | 197 × 256 × 26 mm · 1,16 kg |
| Lengua | Inglés |
| Editor | Mourad, Raphael (Post-doctoral Research Fellow, Post-doctoral Research Fellow, Department of Human Genetics, University of Chicago) |
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