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103
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CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
15 years 5 months ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
WABI
2001
Springer
162views Bioinformatics» more  WABI 2001»
15 years 5 months ago
A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites
A central issue in molecular biology is understanding the regulatory mechanisms that control gene expression. The recent flood of genomic and postgenomic data opens the way for co...
Yoseph Barash, Gill Bejerano, Nir Friedman
100
Voted
CANDT
2009
15 years 4 months ago
Analyzing (social media) networks with NodeXL
We present NodeXL, an extendible toolkit for network overview, discovery and exploration implemented as an add-in to the Microsoft Excel 2007 spreadsheet software. We demonstrate ...
Marc A. Smith, Ben Shneiderman, Natasa Milic-Frayl...
82
Voted
JCSS
2006
56views more  JCSS 2006»
15 years 23 days ago
Determining model accuracy of network traces
Accurate network modeling is critical to the design of network protocols. Traditional modeling approaches, such as Discrete Time Markov Chains (DTMC) are limited in their ability ...
Almudena Konrad, Ben Y. Zhao, Anthony D. Joseph
122
Voted
PR
2006
147views more  PR 2006»
15 years 22 days ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung