- Abstract:
- This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas of graphical models and genetics. The potential of graphical models is explored and illustrated through a number of example applications where the genetic element is substantial or dominating.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
- Publisher:
- Institute of Mathematical Statistics Publisher's website
- Journal:
- Statistical Science Journal website
- Volume:
- 18
- Issue:
- 4
- Pages:
- 489-514
- Publication date:
- 2003-11-05
- ISSN:
-
08834237
- URN:
-
uuid:bb9901d4-63bf-44fa-8d18-47efc8a618fe
- Local pid:
- ora:1953
- Language:
- English
- Keywords:
- Subjects:
- Copyright holder:
- Institute of Mathematical Statistics
- Copyright date:
- 2003
- Notes:
- N. B. Professor Lauritzen was based at Aarlborg University when this article was first published. The full-text of this article is not available in ORA. Citation: Lauritzen, S. L. & Sheehan, N. A. (2003). 'Graphical models for genetic analyses', Statistical Science, 18(4), 489-514. [Available at http://www.imstat.org/sts/].
Journal article
Graphical models for genetic analyses
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