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» Clustering Genes Using Heterogeneous Data Sources
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APBC
2004
132views Bioinformatics» more  APBC 2004»
15 years 4 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
140
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BMCBI
2007
102views more  BMCBI 2007»
15 years 3 months ago
Identification of homologs in insignificant blast hits by exploiting extrinsic gene properties
Background: Homology is a key concept in both evolutionary biology and genomics. Detection of homology is crucial in fields like the functional annotation of protein sequences and...
Jos Boekhorst, Berend Snel
CLUSTER
2006
IEEE
15 years 9 months ago
Heterogeneous Parallel Computing in Remote Sensing Applications: Current Trends and Future Perspectives
Heterogeneous networks of computers have rapidly become a very promising commodity computing solution, expected to play a major role in the design of high performance computing sy...
Antonio J. Plaza
CMSB
2006
Springer
15 years 6 months ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
SEMWEB
2010
Springer
15 years 24 days ago
Summary Models for Routing Keywords to Linked Data Sources
The proliferation of linked data on the Web paves the way to a new generation of applications that exploit heterogeneous data from different sources. However, because this Web of d...
Thanh Tran, Lei Zhang, Rudi Studer