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» Biological Network Inference Using Redundancy Analysis
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BMCBI
2006
202views more  BMCBI 2006»
14 years 9 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
15 years 10 months ago
A visual-analytic toolkit for dynamic interaction graphs
In this article we describe a visual-analytic tool for the interrogation of evolving interaction network data such as those found in social, bibliometric, WWW and biological appli...
Xintian Yang, Sitaram Asur, Srinivasan Parthasarat...
NIPS
1997
14 years 11 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
BMCBI
2010
135views more  BMCBI 2010»
14 years 9 months ago
Delineation of amplification, hybridization and location effects in microarray data yields better-quality normalization
Background: Oligonucleotide arrays have become one of the most widely used high-throughput tools in biology. Due to their sensitivity to experimental conditions, normalization is ...
Marc Hulsman, Anouk Mentink, Eugene P. van Someren...
BMCBI
2007
109views more  BMCBI 2007»
14 years 9 months ago
A domain-based approach to predict protein-protein interactions
Background: Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological proce...
Mudita Singhal, Haluk Resat