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BMCBI
2010
96views more  BMCBI 2010»
15 years 4 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
BMCBI
2006
119views more  BMCBI 2006»
15 years 4 months ago
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip stu
Background: The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with know...
Zihua Hu, Gail R. Willsky
AROBOTS
2002
115views more  AROBOTS 2002»
15 years 4 months ago
Statistical Learning for Humanoid Robots
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata...
BMCBI
2004
141views more  BMCBI 2004»
15 years 4 months ago
Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
Background: Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistical...
Ruslan Sadreyev, Nick V. Grishin
131
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TCAD
2010
150views more  TCAD 2010»
14 years 11 months ago
Voltage and Temperature Aware Statistical Leakage Analysis Framework Using Artificial Neural Networks
Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process paramete...
Janakiraman Viraraghavan, Bharadwaj Amrutur, V. Vi...