Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods

We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets. MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous stati...

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Detalles Bibliográficos
Autores principales: Adler, Priit, Kolde, Raivo, Kull, Meelis, Tkachenko, Aleksandr, Peterson, Hedi, Reimand, Jüri, Vilo, Jaak
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2812946/
https://www.ncbi.nlm.nih.gov/pubmed/19961599
http://dx.doi.org/10.1186/gb-2009-10-12-r139
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author Adler, Priit
Kolde, Raivo
Kull, Meelis
Tkachenko, Aleksandr
Peterson, Hedi
Reimand, Jüri
Vilo, Jaak
author_facet Adler, Priit
Kolde, Raivo
Kull, Meelis
Tkachenko, Aleksandr
Peterson, Hedi
Reimand, Jüri
Vilo, Jaak
author_sort Adler, Priit
collection PubMed
description We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets. MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation. Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns. MEM is freely available at http://biit.cs.ut.ee/mem/.
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spelling pubmed-28129462010-01-29 Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods Adler, Priit Kolde, Raivo Kull, Meelis Tkachenko, Aleksandr Peterson, Hedi Reimand, Jüri Vilo, Jaak Genome Biol Software We present a web resource MEM (Multi-Experiment Matrix) for gene expression similarity searches across many datasets. MEM features large collections of microarray datasets and utilizes rank aggregation to merge information from different datasets into a single global ordering with simultaneous statistical significance estimation. Unique features of MEM include automatic detection, characterization and visualization of datasets that includes the strongest coexpression patterns. MEM is freely available at http://biit.cs.ut.ee/mem/. BioMed Central 2009 2009-12-04 /pmc/articles/PMC2812946/ /pubmed/19961599 http://dx.doi.org/10.1186/gb-2009-10-12-r139 Text en Copyright ©2009 Adler et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Adler, Priit
Kolde, Raivo
Kull, Meelis
Tkachenko, Aleksandr
Peterson, Hedi
Reimand, Jüri
Vilo, Jaak
Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
title Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
title_full Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
title_fullStr Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
title_full_unstemmed Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
title_short Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
title_sort mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2812946/
https://www.ncbi.nlm.nih.gov/pubmed/19961599
http://dx.doi.org/10.1186/gb-2009-10-12-r139
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