David Rocke

Publication List Details

Period

1999 - 2008

Number

12

Co-Authors

robust non-negative matrix factorization analysis of microarray data (2008)

Paul Fogel, S. Stanley Young, Douglas M. Hawkins, Nathalie Ledirac, David Rocke

Motivation: Modern methods like micro arrays, proteomics and metabolomics often produce data sets where there are many more predictor variables than observations. Research in these areas is often...

Original Papers Extracting Three-way Gene Interactions from Microarray Data Extracting Three-way Gene Interactions from Microarray Data (2008)

Jiexin Zhang, Yuan Ji, Li Zhang, Associate Editor:. Prof, David Rocke

Motivation: It is an important and difficult task to extract gene network information from high throughput genomic data. A common approach is to cluster genes using pair-wise correlation as a...

Dimension Reduction for Classification with Gene Expression Microarray Data (2006)

Dai, Jian J, Lieu, Linh, Rocke, David

An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical...

Dimension Reduction for Classification with Gene Expression Microarray Data (2006)

Dai, Jian J, Lieu, Linh, Rocke, David

An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical...

Dimension Reduction for Classification with Gene Expression Microarray Data (2006)

Dai, Jian J, Lieu, Linh, Rocke, David

An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical...

Dimension Reduction for Classification with Gene Expression Microarray Data (2006)

Dai, Jian J, Lieu, Linh, Rocke, David

An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical...

BIOINFORMATICS Comparing Gene Expression Networks in a Multi-Dimensional Space to Extract Similarities and Differences between Organisms (2006)

Gaëlle Lelandais, Pierre Vincens, Anne Badel-chagnon, Stéphane Vialette, Claude Jacq, Serge Hazout, ...

Motivation: Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes....

1 Data Mining Research: Opportunities and Challenges A Report of three NSF Workshops on Mining Large, Massive, and Distributed (1999)

Robert Grossman, Simon Kasif, Reagan Moore, David Rocke, Jeff Ullman

All opinions, findings, conclusions and recommendations in any material resulting from these workshops are those of the workshops ' participants, and do not necessarily reflect the views of the...

Dimension Reduction for Classification with Gene Expression Microarray Data

Jian Dai, Linh Lieu, David Rocke

An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical...

Refinement of Light-Responsive Transcript Lists Using Rice Oligonucleotide Arrays: Evaluation of Gene-Redundancy

Jung, Ki-Hong, Dardick, Christopher, Bartley, Laura E., Cao, Peijian, Phetsom, Jirapa, Canlas, Patrick, ...

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus...