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COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference

The advent of RNA-sequencing and microarray technologies has led to rapid growth of transcriptome data generated for a wide range of organisms, under various cellular, organ and individual conditions. Since the number of possible combinations of intercellular and extracellular conditions is almost u...

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Autores principales: Obayashi, Takeshi, Kagaya, Yuki, Aoki, Yuichi, Tadaka, Shu, Kinoshita, Kengo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324053/
https://www.ncbi.nlm.nih.gov/pubmed/30462320
http://dx.doi.org/10.1093/nar/gky1155
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author Obayashi, Takeshi
Kagaya, Yuki
Aoki, Yuichi
Tadaka, Shu
Kinoshita, Kengo
author_facet Obayashi, Takeshi
Kagaya, Yuki
Aoki, Yuichi
Tadaka, Shu
Kinoshita, Kengo
author_sort Obayashi, Takeshi
collection PubMed
description The advent of RNA-sequencing and microarray technologies has led to rapid growth of transcriptome data generated for a wide range of organisms, under various cellular, organ and individual conditions. Since the number of possible combinations of intercellular and extracellular conditions is almost unlimited, cataloging all transcriptome conditions would be an immeasurable challenge. Gene coexpression refers to the similarity of gene expression patterns under various conditions, such as disease states, tissue types, and developmental stages. Since the quality of gene coexpression data depends on the quality and quantity of transcriptome data, timely usage of the growing data is key to promoting individual research in molecular biology. COXPRESdb (http://coxpresdb.jp) is a database providing coexpression information for 11 animal species. One characteristic feature of COXPRESdb is its ability to compare multiple coexpression data derived from different transcriptomics technologies and different species, which strongly reduces false positive relationships in individual gene coexpression data. Here, we summarized the current version of this database, including 23 coexpression platforms with the highest-level quality till date. Using various functionalities in COXPRESdb, the new coexpression data would support a broader area of research from molecular biology to medical sciences.
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spelling pubmed-63240532019-01-10 COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference Obayashi, Takeshi Kagaya, Yuki Aoki, Yuichi Tadaka, Shu Kinoshita, Kengo Nucleic Acids Res Database Issue The advent of RNA-sequencing and microarray technologies has led to rapid growth of transcriptome data generated for a wide range of organisms, under various cellular, organ and individual conditions. Since the number of possible combinations of intercellular and extracellular conditions is almost unlimited, cataloging all transcriptome conditions would be an immeasurable challenge. Gene coexpression refers to the similarity of gene expression patterns under various conditions, such as disease states, tissue types, and developmental stages. Since the quality of gene coexpression data depends on the quality and quantity of transcriptome data, timely usage of the growing data is key to promoting individual research in molecular biology. COXPRESdb (http://coxpresdb.jp) is a database providing coexpression information for 11 animal species. One characteristic feature of COXPRESdb is its ability to compare multiple coexpression data derived from different transcriptomics technologies and different species, which strongly reduces false positive relationships in individual gene coexpression data. Here, we summarized the current version of this database, including 23 coexpression platforms with the highest-level quality till date. Using various functionalities in COXPRESdb, the new coexpression data would support a broader area of research from molecular biology to medical sciences. Oxford University Press 2019-01-08 2018-11-20 /pmc/articles/PMC6324053/ /pubmed/30462320 http://dx.doi.org/10.1093/nar/gky1155 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Obayashi, Takeshi
Kagaya, Yuki
Aoki, Yuichi
Tadaka, Shu
Kinoshita, Kengo
COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
title COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
title_full COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
title_fullStr COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
title_full_unstemmed COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
title_short COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
title_sort coxpresdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324053/
https://www.ncbi.nlm.nih.gov/pubmed/30462320
http://dx.doi.org/10.1093/nar/gky1155
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