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BMCBI
2007
207views more  BMCBI 2007»
15 years 6 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
BMCBI
2006
122views more  BMCBI 2006»
15 years 6 months ago
A multivariate prediction model for microarray cross-hybridization
Background: Expression microarray analysis is one of the most popular molecular diagnostic techniques in the post-genomic era. However, this technique faces the fundamental proble...
Yian A. Chen, Cheng-Chung Chou, Xinghua Lu, Elizab...
BMCBI
2004
167views more  BMCBI 2004»
15 years 6 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
PRL
2010
149views more  PRL 2010»
15 years 1 months ago
Adaptive linear models for regression: Improving prediction when population has changed
The general setting of regression analysis is to identify a relationship between a response variable Y and one or several explanatory variables X by using a learning sample. In a ...
Charles Bouveyron, Julien Jacques
PROMISE
2010
15 years 1 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies