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BIOINFORMATICS
2007
83views more  BIOINFORMATICS 2007»
13 years 11 months ago
Exploring biological network structure using exponential random graph models
Motivation: The functioning of biological networks depends in large part on their complex underlying structure. When studying their systemic nature many modeling approaches focus ...
Zachary M. Saul, Vladimir Filkov
FOCS
2008
IEEE
14 years 5 months ago
Mixing Time of Exponential Random Graphs
A plethora of random graph models have been developed in recent years to study a range of problems on networks, driven by the wide availability of data from many social, telecommu...
Shankar Bhamidi, Guy Bresler, Allan Sly
BMCBI
2010
176views more  BMCBI 2010»
13 years 11 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...
CORR
2011
Springer
205views Education» more  CORR 2011»
13 years 5 months ago
Random Walk on Directed Dynamic Graphs
Dynamic graphs have emerged as an appropriate model to capture the changing nature of many modern networks, such as peer-to-peer overlays and mobile ad hoc networks. Most of the re...
Oksana Denysyuk, Luis Rodrigues
ICML
2005
IEEE
14 years 11 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell