Computing gene expression data with a knowledge-based gene clustering approach.
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Summary
The relatively short length of these common cluster lists compared to gene groups generated through typical clustering methods or coexpression networks narrows the search for novel functional genes while increasing the likelihood that they are biologically relevant.
- Type
- article
- Published
- 2010-01-01
- Cited by
- 4
- References
- 38
- OpenAlex
- https://openalex.org/W73072409
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9355281
Keywords
Cluster analysis, Gene, Gene cluster, Computational biology, Cluster (spacecraft)
References
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- Right place, right time
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- A General Framework for Weighted Gene Co-Expression Network Analysis
- The tissue expression pattern of the AtGRP5 regulatory region is controlled by a combination of positive and negative elements
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- Arabidopsis SHORT HYPOCOTYL UNDER BLUE1 Contains SPX and EXS Domains and Acts in Cryptochrome Signaling[W]
- Prediction of functional modules based on comparative genome analysis and Gene Ontology application
- Calmodulin7 Plays an Important Role as Transcriptional Regulator in Arabidopsis Seedling Development[W]
- A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
Cited by
- Downstream effectors of light- and phytochrome-dependent regulation of hypocotyl elongation in Arabidopsis thaliana
- Phytochrome-induced SIG2 expression contributes to photoregulation of phytochrome signalling and photomorphogenesis in Arabidopsis thaliana
- Genomic Clustering of differential DNA methylated regions (epimutations) associated with the epigenetic transgenerational inheritance of disease and phenotypic variation
- Big Data Analytics and Deep Learning in Bioinformatics With Hadoop
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