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BMCBI
2007
160views more  BMCBI 2007»
13 years 8 months ago
Identifying protein complexes directly from high-throughput TAP data with Markov random fields
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
BMCBI
2011
13 years 3 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
KDD
2009
ACM
169views Data Mining» more  KDD 2009»
14 years 9 months ago
COA: finding novel patents through text analysis
In recent years, the number of patents filed by the business enterprises in the technology industry are growing rapidly, thus providing unprecedented opportunities for knowledge d...
Mohammad Al Hasan, W. Scott Spangler, Thomas D. Gr...
WWW
2009
ACM
14 years 1 months ago
Extracting data records from the web using tag path clustering
Fully automatic methods that extract lists of objects from the Web have been studied extensively. Record extraction, the first step of this object extraction process, identifies...
Gengxin Miao, Jun'ichi Tatemura, Wang-Pin Hsiung, ...
ICONIP
2007
13 years 10 months ago
Principal Component Analysis for Sparse High-Dimensional Data
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
Tapani Raiko, Alexander Ilin, Juha Karhunen