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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
| Media | Books Hardcover Book (Book with hard spine and cover) |
| Released | November 25, 2014 |
| ISBN13 | 9780198709022 |
| Publishers | Oxford University Press |
| Pages | 478 |
| Dimensions | 197 × 256 × 26 mm · 1.16 kg |
| Language | English |
| Editor | Mourad, Raphael (Post-doctoral Research Fellow, Post-doctoral Research Fellow, Department of Human Genetics, University of Chicago) |
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