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» Prediction of Contact Maps Using Support Vector Machines
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CORR
2008
Springer
100views Education» more  CORR 2008»
13 years 8 months ago
Learning Isometric Separation Maps
Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensio...
Nikolaos Vasiloglou, Alexander G. Gray, David V. A...
BMCBI
2007
207views more  BMCBI 2007»
13 years 8 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...
MMM
2006
Springer
133views Multimedia» more  MMM 2006»
14 years 2 months ago
A SVM-based personal recommendation system for TV programs
This paper presents a SVM-based prediction approach for constructing personal recommendation system for TV programs. We have applied Support Vector Machine (SVM) to personal predi...
Jin An Xu, Kenji Araki
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
14 years 2 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang