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» Identifying Clusters from Positive Data
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109
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TREC
2004
15 years 4 months ago
Identifying Relevant Full-Text Articles for GO Annotation Without MeSH Terms
Gene Ontology (GO) is a controlled vocabulary. Given a gene product, GO enables scientists to clearly and unambiguously describe specific molecular functions of the gene product, ...
Chih Lee, Wen-Juan Hou, Hsin-Hsi Chen
140
Voted
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
15 years 8 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
148
Voted
PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
15 years 8 months ago
Density-Sensitive Evolutionary Clustering
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Maoguo Gong, Licheng Jiao, Ling Wang, Liefeng Bo
131
Voted
BMCBI
2008
133views more  BMCBI 2008»
15 years 2 months ago
CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated
Background: The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false po...
Matthew S. Hestand, Michiel van Galen, Michel P. V...
155
Voted
SDM
2004
SIAM
253views Data Mining» more  SDM 2004»
15 years 4 months ago
Density-Connected Subspace Clustering for High-Dimensional Data
Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective ...
Peer Kröger, Hans-Peter Kriegel, Karin Kailin...