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» Two-phase clustering strategy for gene expression data sets
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RECOMB
2010
Springer
15 years 4 months ago
Hierarchical Generative Biclustering for MicroRNA Expression Analysis
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
José Caldas, Samuel Kaski
BMCBI
2010
106views more  BMCBI 2010»
14 years 9 months ago
Selection of optimal reference genes for normalization in quantitative RT-PCR
Background: Normalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introdu...
Inna Chervoneva, Yanyan Li, Stephanie Schulz, Sean...
BMCBI
2002
89views more  BMCBI 2002»
14 years 9 months ago
Sources of variability and effect of experimental approach on expression profiling data interpretation
Background: We provide a systematic study of the sources of variability in expression profiling data using 56 RNAs isolated from human muscle biopsies (34 Affymetrix MuscleChip ar...
Marina Bakay, Yi-Wen Chen, Rehannah H. A. Borup, P...
ICDM
2003
IEEE
111views Data Mining» more  ICDM 2003»
15 years 2 months ago
OP-Cluster: Clustering by Tendency in High Dimensional Space
Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the definition of similari...
Jinze Liu, Wei Wang 0010
NIPS
2004
14 years 11 months ago
Joint Probabilistic Curve Clustering and Alignment
Clustering and prediction of sets of curves is an important problem in many areas of science and engineering. It is often the case that curves tend to be misaligned from each othe...
Scott Gaffney, Padhraic Smyth