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...
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...
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...
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 ...
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...