Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubWeight™: 0.75‹?›

🔗 View Article (PMC 4667498)

Published in BMC Genomics on December 01, 2015

Authors

Dingming Wu1, Dongfang Wang1, Michael Q Zhang2,3, Jin Gu4

Author Affiliations

1: MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division & Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China.
2: MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division & Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China. michael.zhang@utdallas.edu.
3: Department of Biological Sciences, Center for Systems Biology, University of Texas at Dallas, Richardson, TX, 75080, USA. michael.zhang@utdallas.edu.
4: MOE Key Laboratory of Bioinformatics, TNLIST Bioinformatics Division & Center for Synthetic and Systems Biology, Department of Automation, Tsinghua University, Beijing, 100084, China. jgu@tsinghua.edu.cn.

Articles cited by this

Hallmarks of cancer: the next generation. Cell (2011) 140.01

The hallmarks of cancer. Cell (2000) 113.05

Cancer statistics, 2014. CA Cancer J Clin (2014) 72.81

Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer (2014) 40.30

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature (2012) 31.78

International network of cancer genome projects. Nature (2010) 20.35

COSMIC: exploring the world's knowledge of somatic mutations in human cancer. Nucleic Acids Res (2014) 10.77

The causes and consequences of genetic heterogeneity in cancer evolution. Nature (2013) 5.91

Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis. Bioinformatics (2009) 4.21

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell (2014) 4.17

Tumour heterogeneity in the clinic. Nature (2013) 3.92

Gene expression phenotypic models that predict the activity of oncogenic pathways. Nat Genet (2003) 3.78

Partial Cox regression analysis for high-dimensional microarray gene expression data. Bioinformatics (2004) 1.90

A novel computational framework for simultaneous integration of multiple types of genomic data to identify microRNA-gene regulatory modules. Bioinformatics (2011) 1.68

Pattern discovery and cancer gene identification in integrated cancer genomic data. Proc Natl Acad Sci U S A (2013) 1.60

Dimension reduction methods for microarrays with application to censored survival data. Bioinformatics (2004) 1.53

Integrative analysis of genome-scale data by using pseudoinverse projection predicts novel correlation between DNA replication and RNA transcription. Proc Natl Acad Sci U S A (2004) 1.47

Discovery of multi-dimensional modules by integrative analysis of cancer genomic data. Nucleic Acids Res (2012) 1.46

Hypoxia-simulating agents and selective stimulation of arsenic trioxide-induced growth arrest and cell differentiation in acute promyelocytic leukemic cells. Haematologica (2005) 1.44

The UCSC Cancer Genomics Browser: update 2015. Nucleic Acids Res (2014) 1.44

JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES. Ann Appl Stat (2013) 1.24

Patient-specific data fusion defines prognostic cancer subtypes. PLoS Comput Biol (2011) 1.16

Biological subtypes of breast cancer: Prognostic and therapeutic implications. World J Clin Oncol (2014) 1.16

Bayesian consensus clustering. Bioinformatics (2013) 1.10

Patterns and processes of somatic mutations in nine major cancers. BMC Med Genomics (2014) 1.08

Classification of acute leukaemias. Blood Rev (1988) 0.83

Tumor characterization and stratification by integrated molecular profiles reveals essential pan-cancer features. BMC Genomics (2015) 0.80

Piecewise-constant and low-rank approximation for identification of recurrent copy number variations. Bioinformatics (2014) 0.78