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» A taxonomy of biologically inspired research in computer net...
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PR
2011
12 years 10 months ago
A survey of multilinear subspace learning for tensor data
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
BMCBI
2008
104views more  BMCBI 2008»
13 years 7 months ago
InteroPORC: an automated tool to predict highly conserved protein interaction networks
teps. First, we abstracted protein interactions onto orthologous cluster links. For a given source interaction, if both proteins belonged to a cluster, we constructed a link betwee...
Magali Michaut, Samuel Kerrien, Luisa Montecchi-Pa...
BMCBI
2010
232views more  BMCBI 2010»
13 years 7 months ago
LucidDraw: Efficiently visualizing complex biochemical networks within MATLAB
Background: Biochemical networks play an essential role in systems biology. Rapidly growing network data and e research activities call for convenient visualization tools to aid i...
Sheng He, Juan Mei, Guiyang Shi, Zhengxiang Wang, ...
IJCNN
2006
IEEE
14 years 1 months ago
In-Place Learning for Positional and Scale Invariance
— In-place learning is a biologically inspired concept, meaning that the computational network is responsible for its own learning. With in-place learning, there is no need for a...
Juyang Weng, Hong Lu, Tianyu Luwang, Xiangyang Xue
IJCNN
2006
IEEE
14 years 1 months ago
Optimal In-Place Learning and the Lobe Component Analysis
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
Juyang Weng, Nan Zhang 0002