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BMCBI
2005
118views more  BMCBI 2005»
15 years 3 months ago
Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes
Background: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be us...
Thanyaluk Jirapech-Umpai, J. Stuart Aitken
103
Voted
COMBINATORICS
1999
90views more  COMBINATORICS 1999»
15 years 3 months ago
New Bounds for Codes Identifying Vertices in Graphs
Let G = (V, E) be an undirected graph. Let C be a subset of vertices that we shall call a code. For any vertex v V , the neighbouring set N(v, C) is the set of vertices of C at d...
Gérard D. Cohen, Iiro S. Honkala, Antoine L...
118
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TIT
1998
127views more  TIT 1998»
15 years 3 months ago
On a New Class of Codes for Identifying Vertices in Graphs
—We investigate a new class of codes for the optimal covering of vertices in an undirected graph Gsuch that any vertex in G can be uniquely identified by examining the vertices ...
Mark G. Karpovsky, Krishnendu Chakrabarty, Lev B. ...
128
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PVLDB
2008
134views more  PVLDB 2008»
15 years 3 months ago
Reasoning and identifying relevant matches for XML keyword search
Keyword search is a user-friendly mechanism for retrieving XML data in web and scientific applications. An intuitively compelling but vaguely defined goal is to identify matches t...
Ziyang Liu, Yi Chen
126
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CORR
2010
Springer
134views Education» more  CORR 2010»
15 years 2 months ago
Locally identifying coloring of graphs
Let G = (V, E) be a graph. Let c : V → N be a vertex-coloring of the vertices of G. For any vertex u, we denote by N[u] its closed neighborhood (u and its adjacent vertices), an...
Louis Esperet, Sylvain Gravier, Mickaël Monta...