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» The Spatially-Dispersed Genetic Algorithm
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KDD
2009
ACM
132views Data Mining» more  KDD 2009»
14 years 8 months ago
Learning patterns in the dynamics of biological networks
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
KDD
2008
ACM
206views Data Mining» more  KDD 2008»
14 years 7 months ago
Identifying biologically relevant genes via multiple heterogeneous data sources
Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioin...
Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Y...
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 7 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 7 months ago
Transforming data to satisfy privacy constraints
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...
Vijay S. Iyengar
RECOMB
2003
Springer
14 years 7 months ago
Large scale reconstruction of haplotypes from genotype data
Critical to the understanding of the genetic basis for complex diseases is the modeling of human variation. Most of this variation can be characterized by single nucleotide polymo...
Eleazar Eskin, Eran Halperin, Richard M. Karp