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    Bioinformatics. 2006 May 1;22(9):1144-6. Epub 2006 Mar 13.

    BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data.

    Marioni JC, Thorne NP, Tavaré S.

    Hutchison-MRC Research Centre, Department of Oncology, Computational Biology Group, University of Cambridge Hills Road, Cambridge. J.Marioni@damtp.cam.ac.uk

    SUMMARY: We have developed a new method (BioHMM) for segmenting array comparative genomic hybridization data into states with the same underlying copy number. By utilizing a heterogeneous hidden Markov model, BioHMM incorporates relevant biological factors (e.g. the distance between adjacent clones) in the segmentation process.

    PMID: 16533818 [PubMed - indexed for MEDLINE]

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