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» Evaluation of clustering algorithms for gene expression data
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SEDE
2008
15 years 8 months ago
Improving Fuzzy Algorithms for Automatic Magnetic Resonance Image Segmentation
: In this paper, we present reliable algorithms for fuzzy k-means and C-means that could improve MRI segmentation. Since the k-means or FCM method aims to minimize the sum of squar...
Ennumeri A. Zanaty, Sultan Aljahdali, Narayan C. D...
BMCBI
2007
152views more  BMCBI 2007»
15 years 6 months ago
Bioinformatic identification of novel putative photoreceptor specific cis-elements
Background: Cell specific gene expression is largely regulated by different combinations of transcription factors that bind cis-elements in the upstream promoter sequence. However...
Charles G. Danko, Vera A. McIlvain, Maochun Qin, B...
BMCBI
2007
197views more  BMCBI 2007»
15 years 6 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
BMCBI
2006
104views more  BMCBI 2006»
15 years 6 months ago
Semi-supervised discovery of differential genes
Background: Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditio...
Shigeyuki Oba, Shin Ishii
ICDM
2005
IEEE
150views Data Mining» more  ICDM 2005»
16 years 6 days ago
Combining Multiple Clusterings by Soft Correspondence
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu