Literature DB >> 12715832

Clustering-based approaches to discovering and visualising microarray data patterns.

Francisco Azuaje1.   

Abstract

This article focuses on clustering techniques for the analysis of microarray data and discusses contributions and applications for the implementation of intelligent diagnostic systems and therapy design studies. Approaches to validating and visualising expression clustering results and software and other relevant resources to support clustering-based analyses are reviewed. Finally, this paper addresses current limitations and problems that need to be investigated for the development of an advanced generation of pattern discovery tools.

Mesh:

Year:  2003        PMID: 12715832     DOI: 10.1093/bib/4.1.31

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  5 in total

1.  Specialization versus adaptation: two strategies employed by cyanophages to enhance their translation efficiencies.

Authors:  Keren Limor-Waisberg; Asaf Carmi; Avigdor Scherz; Yitzhak Pilpel; Itay Furman
Journal:  Nucleic Acids Res       Date:  2011-04-05       Impact factor: 16.971

2.  An effective non-parametric method for globally clustering genes from expression profiles.

Authors:  Jingyu Hou; Wei Shi; Gang Li; Wanlei Zhou
Journal:  Med Biol Eng Comput       Date:  2007-10-18       Impact factor: 3.079

3.  Non-linear mapping for exploratory data analysis in functional genomics.

Authors:  Francisco Azuaje; Haiying Wang; Alban Chesneau
Journal:  BMC Bioinformatics       Date:  2005-01-20       Impact factor: 3.169

4.  Computational gene expression profiling under salt stress reveals patterns of co-expression.

Authors:  Ashok Sharma
Journal:  Genom Data       Date:  2016-01-15

5.  Comparative transcriptomic analysis of contrasting hybrid cultivars reveal key drought-responsive genes and metabolic pathways regulating drought stress tolerance in maize at various stages.

Authors:  Songtao Liu; Tinashe Zenda; Jiao Li; Yafei Wang; Xinyue Liu; Huijun Duan
Journal:  PLoS One       Date:  2020-10-15       Impact factor: 3.240

  5 in total

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