de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Talk

Machine Learning Algorithms for Polymorphism Detection

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons84204

Schweikert,  G
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84193

Zeller G, Clark R, Ossowski S, Warthmann N, Shinn P, Frazer K, Ecker J, Huson D, Weigel D, Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84153

Rätsch,  G
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Schweikert, G., Zeller G, Clark R, Ossowski S, Warthmann N, Shinn P, Frazer K, Ecker J, Huson D, Weigel D, Schölkopf, B., & Rätsch, G. (2006). Machine Learning Algorithms for Polymorphism Detection. Talk presented at 2nd ISCB Student Council Symposium. Fortaleza, Brazil.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-D0C3-0
Abstract
Analyzing resequencing array data using machine learning, we obtain a genome-wide inventory of polymorphisms in 20 wild strains of Arabidopsis thaliana, including 750,000 single nucleotide poly- morphisms (SNPs) and thousands of highly polymorphic regions and deletions. We thus provide an unprecedented resource for the study of natural variation in plants.