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» Evaluation of clustering algorithms for gene expression data
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BMCBI
2007
152views more  BMCBI 2007»
14 years 9 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
AIIA
2009
Springer
15 years 4 months ago
Ontology-Driven Co-clustering of Gene Expression Data
Abstract. The huge volume of gene expression data produced by microarrays and other high-throughput techniques has encouraged the development of new computational techniques to eva...
Francesca Cordero, Ruggero G. Pensa, Alessia Visco...
BMEI
2008
IEEE
14 years 11 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...
AI
2006
Springer
15 years 1 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
15 years 3 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...