Add to ORKGSelf organizing maps (SOMs) portrait molecular phenotypes with individual resolution. We demonstrate the potency of the method in selected applications characterizing the diver-sity of gene expression in different tissues and cancer sub-types, mRNA and miRNA fingerprints of stem cells, the proteome landscape of algae and genomic relations between humans from different populations. It is further shown that SOM portraiting provides a comprehensive frame to de-scribe development, differentiation and diversity in space and/or time.
AbstractDNA microarray technologies together with rapidly increasing genomic sequence information is...
A self-organizing map (SOM) is an artificial neural network algorithm that can learn from the traini...
Gene expression atlases have transformed our understanding of the development, composition and funct...
Self organizing maps (SOMs) portrait molecular phenotypes with individual resolution. We demonstrate...
Modern high-throughput technologies such as microarrays, next generation sequencing and mass spectro...
We tested whether Self-Organizing Maps (SOMs) could be used to effectively integrate, visualize, and...
* to whom correspondence should be addressed Background: Self organizing maps (SOM) enable the strai...
A method to evaluate and analyze the massive data generated by series of microarray experiments is o...
cDNA microarrays permit massively parallel gene expression analysis and have spawned a new paradigm ...
Background: 
Self organizing maps (SOM) enable the straightforward portraying of high-dimen...
We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and...
Despite our rapidly growing knowledge about the human genome, we do not know all of the genes requir...
AbstractWe describe a powerful approach, component plane presentation integrated self-organizing map...
<p>Genes that were differentially expressed either across or within groups comparisons at different ...
Gene expression atlases have transformed our understanding of the development, composition and funct...
AbstractDNA microarray technologies together with rapidly increasing genomic sequence information is...
A self-organizing map (SOM) is an artificial neural network algorithm that can learn from the traini...
Gene expression atlases have transformed our understanding of the development, composition and funct...
Self organizing maps (SOMs) portrait molecular phenotypes with individual resolution. We demonstrate...
Modern high-throughput technologies such as microarrays, next generation sequencing and mass spectro...
We tested whether Self-Organizing Maps (SOMs) could be used to effectively integrate, visualize, and...
* to whom correspondence should be addressed Background: Self organizing maps (SOM) enable the strai...
A method to evaluate and analyze the massive data generated by series of microarray experiments is o...
cDNA microarrays permit massively parallel gene expression analysis and have spawned a new paradigm ...
Background: 
Self organizing maps (SOM) enable the straightforward portraying of high-dimen...
We tested whether self-organizing maps (SOMs) could be used to effectively integrate, visualize, and...
Despite our rapidly growing knowledge about the human genome, we do not know all of the genes requir...
AbstractWe describe a powerful approach, component plane presentation integrated self-organizing map...
<p>Genes that were differentially expressed either across or within groups comparisons at different ...
Gene expression atlases have transformed our understanding of the development, composition and funct...
AbstractDNA microarray technologies together with rapidly increasing genomic sequence information is...
A self-organizing map (SOM) is an artificial neural network algorithm that can learn from the traini...
Gene expression atlases have transformed our understanding of the development, composition and funct...