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» Measuring the Similarity of Labeled Graphs
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PAMI
2006
206views more  PAMI 2006»
13 years 9 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
FLAIRS
2006
13 years 11 months ago
Inexact Graph Matching: A Case of Study
Inexact graph matching has become an important research area because it is used to find similarities among objects in several real domains such as chemical and biological compound...
Ivan Olmos, Jesus A. Gonzalez, Mauricio Osorio
BMCBI
2008
173views more  BMCBI 2008»
13 years 9 months ago
Gene Vector Analysis (Geneva): A unified method to detect differentially-regulated gene sets and similar microarray experiments
Background: Microarray experiments measure changes in the expression of thousands of genes. The resulting lists of genes with changes in expression are then searched for biologica...
Stephen W. Tanner, Pankaj Agarwal
BMCBI
2007
93views more  BMCBI 2007»
13 years 9 months ago
The topology of metabolic isotope labeling networks
Background: Metabolic Flux Analysis (MFA) based on isotope labeling experiments (ILEs) is a widely established tool for determining fluxes in metabolic pathways. Isotope labeling ...
Michael Weitzel, Wolfgang Wiechert, Katharina N&ou...
ICPR
2004
IEEE
14 years 10 months ago
A Probabilistic Approach to Learning Costs for Graph Edit Distance
Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies ...
Horst Bunke, Michel Neuhaus