142 citations · 143 across the 3 of their papers we have counts for
3 papers
Topical Hidden Genome: Discovering Latent Cancer Mutational Topics using a Bayesian Multilevel Context-learning Approach
Saptarshi Chakraborty, Zoe Guan, Colin B. Begg +1
Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle who…
Using the "Hidden" Genome to Improve Classification of Cancer Types
Saptarshi Chakraborty, Colin B. Begg, Ronglai Shen
It is increasingly common clinically for cancer specimens to be examined using techniques that identify somatic mutations. In principle these mutational profiles can be used to dia…
Sparse integrative clustering of multiple omics data sets
Ronglai Shen, Sijian Wang, Qianxing Mo
High resolution microarrays and second-generation sequencing platforms are powerful tools to investigate genome-wide alterations in DNA copy number, methylation and gene expression…