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» A DIAMOND Method for Classifying Biological Data
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SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
13 years 8 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey
RECOMB
2003
Springer
14 years 7 months ago
Joint classifier and feature optimization for cancer diagnosis using gene expression data
Recent research has demonstrated quite convincingly that accurate cancer diagnosis can be achieved by constructing classifiers that are designed to compare the gene expression pro...
Balaji Krishnapuram, Lawrence Carin, Alexander J. ...
AUSAI
2008
Springer
13 years 9 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
BMCBI
2008
142views more  BMCBI 2008»
13 years 7 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 7 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto