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» On Appropriate Adaptation Levels for the Learning of Gene Li...
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BMCBI
2010
176views more  BMCBI 2010»
13 years 7 months ago
Reverse engineering gene regulatory network from microarray data using linear time-variant model
nd: Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability...
Mitra Kabir, Nasimul Noman, Hitoshi Iba
BMCBI
2008
135views more  BMCBI 2008»
13 years 7 months ago
Ab-origin: an enhanced tool to identify the sourcing gene segments in germline for rearranged antibodies
Background: In the adaptive immune system, variable regions of immunoglobulin (IG) are encoded by random recombination of variable (V), diversity (D), and joining (J) gene segment...
Xiaojing Wang, Di Wu, SiYuan Zheng, Jing Sun, Lin ...
BMCBI
2006
143views more  BMCBI 2006»
13 years 7 months ago
Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms
Background: Microarray technology produces gene expression data on a genomic scale for an endless variety of organisms and conditions. However, this vast amount of information nee...
Rainer König, Gunnar Schramm, Marcus Oswald, ...
COST
2009
Springer
185views Multimedia» more  COST 2009»
13 years 4 months ago
How an Agent Can Detect and Use Synchrony Parameter of Its Own Interaction with a Human?
Synchrony is claimed by psychology as a crucial parameter of any social interaction: to give to human a feeling of natural interaction, a feeling of agency [17], an agent must be a...
Ken Prepin, Philippe Gaussier
RAS
2010
109views more  RAS 2010»
13 years 5 months ago
Combining active learning and reactive control for robot grasping
Grasping an object is a task that inherently needs to be treated in a hybrid fashion. The system must decide both where and how to grasp the object. While selecting where to grasp...
Oliver Krömer, Renaud Detry, Justus H. Piater...