Marioni J C, Thorne N P, Tavaré S
Hutchison-MRC Research Centre, Department of Oncology, Computational Biology Group, University of Cambridge Hills Road, Cambridge.
Bioinformatics. 2006 May 1;22(9):1144-6. doi: 10.1093/bioinformatics/btl089. Epub 2006 Mar 13.
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.
我们开发了一种新方法(生物隐马尔可夫模型),用于将阵列比较基因组杂交数据分割成具有相同潜在拷贝数的状态。通过利用异质隐马尔可夫模型,生物隐马尔可夫模型在分割过程中纳入了相关生物学因素(例如相邻克隆之间的距离)。