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BMCBI
2010
176views more  BMCBI 2010»
13 years 7 months ago
Bayesian statistical modelling of human protein interaction network incorporating protein disorder information
Background: We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive app...
Svetlana Bulashevska, Alla Bulashevska, Roland Eil...
CCS
2009
ACM
14 years 1 months ago
Learning your identity and disease from research papers: information leaks in genome wide association study
Genome-wide association studies (GWAS) aim at discovering the association between genetic variations, particularly single-nucleotide polymorphism (SNP), and common diseases, which...
Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang,...
BIOCOMP
2006
13 years 8 months ago
An Artificial Neural Network based Model to Analyze Malarial Data and Predict Organ Failure
Health Care Management is one of the most important and most important research areas of the new millennium. The main purpose of this work was to analyze the data on malaria patie...
Dinesh P. Mital, Shankar Srinivasan, Syed Haque, R...
PROCEDIA
2010
153views more  PROCEDIA 2010»
13 years 5 months ago
Conceptual framework for dynamic trust monitoring and prediction
The dynamic and collaborative nature of mobile and sensor networks raises the issue of how connected mobile devices can be trusted. Despite the existing security paradigms such as...
Olufunmilola Onolaja, Rami Bahsoon, Georgios Theod...
SPRINGSIM
2007
13 years 8 months ago
Modeling and analysis of worm defense using stochastic activity networks
— Stochastic activity networks (SANs) are a widely used formalism for describing complex systems that have random behavior. Sophisticated software tools exist for the modeling an...
David M. Nicol, Steve Hanna, Frank Stratton, Willi...