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» Identifying graphs from noisy and incomplete data
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BMCBI
2006
118views more  BMCBI 2006»
13 years 7 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
WWW
2008
ACM
14 years 8 months ago
Behavioral classification on the click graph
A bipartite query-URL graph, where an edge indicates that a document was clicked for a query, is a useful construct for finding groups of related queries and URLs. Here we use thi...
Martin Szummer, Nick Craswell
SIGMETRICS
2008
ACM
115views Hardware» more  SIGMETRICS 2008»
13 years 7 months ago
Densification arising from sampling fixed graphs
During the past decade, a number of different studies have identified several peculiar properties of networks that arise from a diverse universe, ranging from social to computer n...
Pedram Pedarsani, Daniel R. Figueiredo, Matthias G...
BMCBI
2010
144views more  BMCBI 2010»
13 years 7 months ago
Finding sRNA generative locales from high-throughput sequencing data with NiBLS
Background: Next-generation sequencing technologies allow researchers to obtain millions of sequence reads in a single experiment. One important use of the technology is the seque...
Daniel MacLean, Vincent Moulton, David J. Studholm...
PKDD
2004
Springer
147views Data Mining» more  PKDD 2004»
14 years 29 days ago
Using a Hash-Based Method for Apriori-Based Graph Mining
The problem of discovering frequent subgraphs of graph data can be solved by constructing a candidate set of subgraphs first, and then, identifying within this candidate set those...
Phu Chien Nguyen, Takashi Washio, Kouzou Ohara, Hi...