Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
17
click to vote
JIB
2007
favorite
Email
discuss
report
68
views
more
JIB 2007
»
Supervised classification of combined copy number and gene expression data
13 years 8 months ago
Download
mpba.fbk.eu
Samantha Riccadonna, Giuseppe Jurman, Stefano Merl
Real-time Traffic
JIB 2007
|
claim paper
Related Content
»
Recursive Cluster Elimination RCE for classification and feature selection from gene expre...
»
Crossplatform analysis of cancer microarray data improves gene expression based classifica...
»
Classification of arrayCGH data using fused SVM
»
Gene selection for classification of microarray data based on the Bayes error
»
Combined Gene Selection Methods for Microarray Data Analysis
»
Analysis of Gene Expression Microarrays for Phenotype Classification
»
Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression
»
Prediction potential of candidate biomarker sets identified and validated on gene expressi...
»
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
more »
Post Info
More Details (n/a)
Added
15 Dec 2010
Updated
15 Dec 2010
Type
Journal
Year
2007
Where
JIB
Authors
Samantha Riccadonna, Giuseppe Jurman, Stefano Merler, Silvano Paoli, A. Quattrone, Cesare Furlanello
Comments
(0)
Researcher Info
JIB 2006 Study Group
Computer Vision