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BMCBI
2005
112views more  BMCBI 2005»
14 years 9 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
BMCBI
2008
125views more  BMCBI 2008»
14 years 10 months ago
Exploration and visualization of gene expression with neuroanatomy in the adult mouse brain
Background: Spatially mapped large scale gene expression databases enable quantitative comparison of data measurements across genes, anatomy, and phenotype. In most ongoing effort...
Christopher Lau, Lydia Ng, Carol Thompson, Sayan D...
BMCBI
2010
115views more  BMCBI 2010»
14 years 10 months ago
Integration of multiple data sources to prioritize candidate genes using discounted rating system
Background: Identifying disease gene from a list of candidate genes is an important task in bioinformatics. The main strategy is to prioritize candidate genes based on their simil...
Yongjin Li, Jagdish Chandra Patra
IDA
2007
Springer
14 years 9 months ago
An unsupervised clustering approach for leukaemia classification based on DNA micro-arrays data
: DNA micro-arrays provide thousands of genomic expressions on the same subject. A main issue is then to find the subset of genes whose degeneration is responsible of a certain typ...
Simone Garatti, Sergio Bittanti, Diego Liberati, A...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
15 years 3 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali