Integrative clustering methods for high-dimensional molecular data

• Published in: Translational cancer research Vol. 3; no. 3; pp. 202 - 216
• Main Authors: Chalise, Prabhakar, Koestler, Devin C, Bimali, Milan, Yu, Qing, Fridley, Brooke L
• Format: Journal Article
• Language: English
• Published: China 01.06.2014
• Subjects: cophenetic correlation; mixture models; latent models; non-negative matrix factorization; Consensus clustering

High-throughput 'omic' data, such as gene expression, DNA methylation, DNA copy number, has played an instrumental role in furthering our understanding of the molecular basis in states of human health and disease. As cells with similar morphological characteristics can exhibit entirely dif...