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Literature DB >> 16533818

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

Abstract

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.

Mesh：

Year: 2006 PMID： 16533818 DOI： 10.1093/bioinformatics/btl089

Source DB: PubMed Journal: Bioinformatics ISSN： 1367-4803 Impact factor: 6.937

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Cited

65 in total

1. A double-layered mixture model for the joint analysis of DNA copy number and gene expression data.

Authors: Hyungwon Choi; Zhaohui S Qin; Debashis Ghosh
Journal: J Comput Biol Date: 2010-02 Impact factor: 1.479

2. An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma.

Authors: Pavel Sumazin; Xuerui Yang; Hua-Sheng Chiu; Wei-Jen Chung; Archana Iyer; David Llobet-Navas; Presha Rajbhandari; Mukesh Bansal; Paolo Guarnieri; Jose Silva; Andrea Califano
Journal: Cell Date: 2011-10-14 Impact factor: 41.582

3. Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

Authors: Roger Pique-Regi; Jordi Monso-Varona; Antonio Ortega; Robert C Seeger; Timothy J Triche; Shahab Asgharzadeh
Journal: Bioinformatics Date: 2008-01-18 Impact factor: 6.937

4. PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data.

Authors: Kai Wang; Mingyao Li; Dexter Hadley; Rui Liu; Joseph Glessner; Struan F A Grant; Hakon Hakonarson; Maja Bucan
Journal: Genome Res Date: 2007-10-05 Impact factor: 9.043

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

1. A double-layered mixture model for the joint analysis of DNA copy number and gene expression data.

2. An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma.

3. Sparse representation and Bayesian detection of genome copy number alterations from microarray data.

4. PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data.

5. Application of signal processing techniques for estimating regions of copy number variations in human meningioma DNA.

6. An improved method for detecting and delineating genomic regions with altered gene expression in cancer.

7. Bayesian DNA copy number analysis.

8. Using Free and Open-Source Bioconductor Packages to Analyze Array Comparative Genomics Hybridization (aCGH) Data.

9. Normalized, segmented or called aCGH data?

Review 10. Cancer gene discovery in mouse and man.