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» Semantic Mining and Analysis of Gene Expression Data
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BMCBI
2008
122views more  BMCBI 2008»
14 years 10 months ago
Reconstructing networks of pathways via significance analysis of their intersections
Background: Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statist...
Mirko Francesconi, Daniel Remondini, Nicola Nerett...
BMCBI
2010
162views more  BMCBI 2010»
14 years 10 months ago
Moara: a Java library for extracting and normalizing gene and protein mentions
Background: Gene/protein recognition and normalization are important preliminary steps for many biological text mining tasks, such as information retrieval, protein-protein intera...
Mariana L. Neves, José María Carazo,...
BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
14 years 10 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang
WISE
2005
Springer
15 years 3 months ago
A Web Recommendation Technique Based on Probabilistic Latent Semantic Analysis
Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of clickstream data will lead to capture usag...
Guandong Xu, Yanchun Zhang, Xiaofang Zhou
CVPR
2008
IEEE
15 years 12 months ago
A unified framework for generalized Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is one of the wellknown methods for supervised dimensionality reduction. Over the years, many LDA-based algorithms have been developed to cope w...
Shuiwang Ji, Jieping Ye