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SUMMARY:An algorithm to segment count data using a binomial negative model
  - Rigaill\, G (INRA-CNRS-Universit d'Evry Val d'Essonne\, URGV)
DTSTART:20140116T100000Z
DTEND:20140116T103000Z
UID:TALK49979@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:We consider the problem of segmenting a count data profile. We
  developed an algorithm to recover the best (w.r.t the likelihood) segment
 ations in 1 to K_{max} segments. We prove that the optimal segmentation ca
 n be recovered using a compression scheme which reduces the time complexit
 y. The compression is particularly efficient when the signal has large pla
 teaus. We illustrate our algorithm on next generation sequencing data.\n
LOCATION:Seminar Room 1\, Newton Institute
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