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158views more  PRL 2010»
12 years 10 days ago
Data clustering: 50 years beyond K-means
: Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organ...
Anil K. Jain
12 years 1 months ago
A framework for privacy-preserving cluster analysis
Abstract--Releasing person-specific data could potentially reveal sensitive information of individuals. k-anonymization is a promising privacy protection mechanism in data publishi...
Benjamin C. M. Fung, Ke Wang, Lingyu Wang, Mourad ...
103views more  CSDA 2007»
12 years 1 months ago
Cluster-wise assessment of cluster stability
Stability in cluster analysis is strongly dependent on the data set, especially on how well separated and how homogeneous the clusters are. In the same clustering, some clusters m...
Christian Hennig
114views more  DATAMINE 2002»
12 years 1 months ago
Techniques of Cluster Algorithms in Data Mining
An overview of cluster analysis techniques from a data mining point of view is given. This is done by a strict separation of the questions of various similarity and distance measur...
Johannes Grabmeier, Andreas Rudolph
108views more  CLASSIFICATION 2006»
12 years 2 months ago
The Practice of Cluster Analysis
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Jon R. Kettenring
149views more  BMCBI 2006»
12 years 2 months ago
HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteri
Background: Accurate interpretation of data obtained by unsupervised analysis of large scale expression profiling studies is currently frequently performed by visually combining s...
Roel G. W. Verhaak, Mathijs A. Sanders, Maarten A....
153views more  BMCBI 2010»
12 years 2 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
94views more  BMCBI 2010»
12 years 2 months ago
A comparative study of conservation and variation scores
Background: Conservation and variation scores are used when evaluating sites in a multiple sequence alignment, in order to identify residues critical for structure or function. A ...
Fredrik Johansson, Hiroyuki Toh
75views more  BIOSYSTEMS 2008»
12 years 2 months ago
Using matrix of thresholding partial correlation coefficients to infer regulatory network
DNA arrays measure the expression levels for thousands of genes simultaneously under different conditions. These measurements reflect many aspects of the underlying biological pro...
Lide Han, Jun Zhu
125views more  BMCBI 2010»
12 years 2 months ago
NeatMap - non-clustering heat map alternatives in R
Background: The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the ...
Satwik Rajaram, Yoshi Oono