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» Clustering Genes Using Heterogeneous Data Sources
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BMCBI
2005
103views more  BMCBI 2005»
14 years 11 months ago
Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments
Background: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage o...
Hua Liu, Sergey Tarima, Aaron S. Borders, Thomas V...
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 2 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
NAR
2008
114views more  NAR 2008»
14 years 11 months ago
ENDEAVOUR update: a web resource for gene prioritization in multiple species
ENDEAVOUR (http://www.esat.kuleuven.be/endeavour web; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of ca...
Léon-Charles Tranchevent, Roland Barriot, S...
PAKDD
2010
ACM
158views Data Mining» more  PAKDD 2010»
15 years 4 months ago
Integrative Parameter-Free Clustering of Data with Mixed Type Attributes
Abstract. Integrative mining of heterogeneous data is one of the major challenges for data mining in the next decade. We address the problem of integrative clustering of data with ...
Christian Böhm, Sebastian Goebl, Annahita Osw...
AAAI
1996
15 years 1 months ago
Learning Models for Multi-Source Integration
One issue involved in accessing multiple heterogeneous information sources is how to integrate the retrieved data. SIMS, an information mediator, handles this problem by mapping t...
Sheila Tejada, Craig A. Knoblock, Steven Minton