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» Evaluation of clustering algorithms for gene expression data
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ACSC
2009
IEEE
15 years 8 months ago
Inference of Gene Expression Networks Using Memetic Gene Expression Programming
In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression n...
Armita Zarnegar, Peter Vamplew, Andrew Stranieri
CIKM
2006
Springer
15 years 5 months ago
Mining coherent patterns from heterogeneous microarray data
Microarray technology is a powerful tool for geneticists to monitor interactions among tens of thousands of genes simultaneously. There has been extensive research on coherent sub...
Xiang Zhang, Wei Wang 0010
BMCBI
2004
158views more  BMCBI 2004»
15 years 1 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
BMCBI
2007
123views more  BMCBI 2007»
15 years 1 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
VLDB
2004
ACM
143views Database» more  VLDB 2004»
15 years 6 months ago
GPX: Interactive Mining of Gene Expression Data
Discovering co-expressed genes and coherent expression patterns in gene expression data is an important data analysis task in bioinformatics research and biomedical applications. ...
Daxin Jiang, Jian Pei, Aidong Zhang