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» On the Effectiveness of Constraints Sets in Clustering Genes
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ICML
2000
IEEE
15 years 10 months ago
Clustering with Instance-level Constraints
Clustering algorithms conduct a search through the space of possible organizations of a data set. In this paper, we propose two types of instance-level clustering constraints ? mu...
Kiri Wagstaff, Claire Cardie
BIBE
2007
IEEE
127views Bioinformatics» more  BIBE 2007»
15 years 1 months ago
Gene Selection via Matrix Factorization
The recent development of microarray gene expression techniques have made it possible to offer phenotype classification of many diseases. However, in gene expression data analysis...
Fei Wang, Tao Li
KDD
2003
ACM
152views Data Mining» more  KDD 2003»
15 years 9 months ago
Interactive exploration of coherent patterns in time-series gene expression data
Discovering coherent gene expression patterns in time-series gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we pr...
Daxin Jiang, Jian Pei, Aidong Zhang
BMCBI
2008
167views more  BMCBI 2008»
14 years 9 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren
RECOMB
1997
Springer
15 years 1 months ago
Progressive multiple alignment with constraints
A progressive alignment algorithm produces a multi-alignment of a set of sequences by repeatedly aligning pairs of sequences and/or previously generated alignments. We describe a ...
Gene Myers, Sanford Selznick, Zheng Zhang 0004, We...