Discovering maximal size coherent biclusters from gene expression data

ISSN： 1368-2156

Source： International Journal of Healthcare Technology and Management, Vol.12, Iss.5-6, 2011-09, pp. : 405-421

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

The ‘miss rate’ for the analysis of gene expression data

By Taylor Jonathan

Biostatistics, Vol. 6, Iss. 1, 2005-01 ,pp. : 111-117

Oxford University Press

Access to resources Recommend Favorite

Classification of patients from time-course gene expression

By Zhang Yuping Tibshirani Robert Davis Ronald

Biostatistics, Vol. 14, Iss. 1, 2013-01 ,pp. : 87-98

Oxford University Press

Access to resources Recommend Favorite

Cluster-based network model for time-course gene expression data

By Inoue Lurdes Y. T. Neira Mauricio Nelson Colleen Gleave Martin Etzioni Ruth

Biostatistics, Vol. 8, Iss. 3, 2007-07 ,pp. : 507-525

Oxford University Press

Access to resources Recommend Favorite

Robust depth-based tools for the analysis of gene expression data

By Lpez-Pintado Sara Romo Juan Torrente Aurora

Biostatistics, Vol. 11, Iss. 2, 2010-04 ,pp. : 254-264

Oxford University Press

Access to resources Recommend Favorite

Mixture models with multiple levels, with application to the analysis of multifactor gene expression data

By Jrnsten Rebecka Kele Sndz

Biostatistics, Vol. 9, Iss. 3, 2008-07 ,pp. : 540-554

Oxford University Press

Access to resources Recommend Favorite