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Database Profile

General information

URL: https://coxpresdb.jp
Full name: Coexpression Database
Description: COXPRESdb provides gene coexpression relationships for animal species.
Year founded: 2008
Last update: 2022-11-03
Version: v8.1
Accessibility:
Manual:
Accessible
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Country/Region: Japan

Contact information

University/Institution: Tohoku University
Address: 6-3-09,Aramaki-Aza-Aoba,Aoba-ku,Sendai 980Ð8679,Japan
City: Sendai
Province/State:
Country/Region: Japan
Contact name (PI/Team): Kengo Kinoshita
Contact email (PI/Helpdesk): kengo@ecei.tohoku.ac.jp

Publications

36350658
COXPRESdb v8: an animal gene coexpression database navigating from a global view to detailed investigations. [PMID: 36350658]
Takeshi Obayashi, Shun Kodate, Himiko Hibara, Yuki Kagaya, Kengo Kinoshita

Gene coexpression is synchronization of gene expression across many cellular and environmental conditions and is widely used to infer the biological function of genes. Gene coexpression information is complex, comprising a complete graph of all genes in the genome, and requires appropriate visualization and analysis tools. Since its initial release in 2007, the animal gene expression database COXPRESdb (https://coxpresdb.jp) has been continuously improved by adding new gene coexpression data and analysis tools. Here, we report COXPRESdb version 8, which has been enhanced with new features for an overview, summary, and individual examination of coexpression relationships: CoexMap to display coexpression on a genome scale, pathway enrichment analysis to summarize the function of coexpressed genes, and CoexPub to bridges coexpression and existing knowledge. COXPRESdb also facilitates downstream analyses such as interspecies comparisons by integrating RNAseq and microarray coexpression data in a union-type gene coexpression. COXPRESdb strongly support users with the new coexpression data and enhanced functionality.

Nucleic Acids Res. 2023:51(D1) | 5 Citations (from Europe PMC, 2024-04-06)
30462320
COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference. [PMID: 30462320]
Obayashi T, Kagaya Y, Aoki Y, Tadaka S, Kinoshita K.

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.

Nucleic Acids Res. 2019:47(D1) | 74 Citations (from Europe PMC, 2024-04-20)
25392420
COXPRESdb in 2015: coexpression database for animal species by DNA-microarray and RNAseq-based expression data with multiple quality assessment systems. [PMID: 25392420]
Okamura Y, Aoki Y, Obayashi T, Tadaka S, Ito S, Narise T, Kinoshita K.

The COXPRESdb (http://coxpresdb.jp) provides gene coexpression relationships for animal species. Here, we report the updates of the database, mainly focusing on the following two points. For the first point, we added RNAseq-based gene coexpression data for three species (human, mouse and fly), and largely increased the number of microarray experiments to nine species. The increase of the number of expression data with multiple platforms could enhance the reliability of coexpression data. For the second point, we refined the data assessment procedures, for each coexpressed gene list and for the total performance of a platform. The assessment of coexpressed gene list now uses more reasonable P-values derived from platform-specific null distribution. These developments greatly reduced pseudo-predictions for directly associated genes, thus expanding the reliability of coexpression data to design new experiments and to discuss experimental results. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2015:43(Database issue) | 91 Citations (from Europe PMC, 2024-04-20)
23203868
COXPRESdb: a database of comparative gene coexpression networks of eleven species for mammals. [PMID: 23203868]
Obayashi T, Okamura Y, Ito S, Tadaka S, Motoike IN, Kinoshita K.

Coexpressed gene databases are valuable resources for identifying new gene functions or functional modules in metabolic pathways and signaling pathways. Although coexpressed gene databases are a fundamental platform in the field of plant biology, their use in animal studies is relatively limited. The COXPRESdb (http://coxpresdb.jp) provides coexpression relationships for multiple animal species, as comparisons of coexpressed gene lists can enhance the reliability of gene coexpression determinations. Here, we report the updates of the database, mainly focusing on the following two points. First, we updated our coexpression data by including recent microarray data for the previous seven species (human, mouse, rat, chicken, fly, zebrafish and nematode) and adding four new species (monkey, dog, budding yeast and fission yeast), along with a new human microarray platform. A reliability scoring function was also implemented, based on coexpression conservation to filter out coexpression with low reliability. Second, the network drawing function was updated, to implement automatic cluster analyses with enrichment analyses in Gene Ontology and in cis elements, along with interactive network analyses with Cytoscape Web. With these updates, COXPRESdb will become a more powerful tool for analyses of functional and regulatory networks of genes in a variety of animal species.

Nucleic Acids Res. 2013:41(Database issue) | 57 Citations (from Europe PMC, 2024-04-20)
21081562
COXPRESdb: a database to compare gene coexpression in seven model animals. [PMID: 21081562]
Obayashi T, Kinoshita K.

Publicly available databases of coexpressed gene sets are a valuable resource for a wide variety of experimental studies, including gene targeting for functional identification, and for investigations of regulatory mechanisms or protein-protein interaction networks. Although coexpressed gene databases are becoming more and more popular in the field of plant biology, those with animal data are rather limited, possibly due to the lower reliability of the coexpression data. The original COXPRESdb (coexpressed gene database) (http://coxpresdb.jp) represented the coexpression relationship for human and mouse. Here, we report updates of this database that especially focus on the enhancement of the reliability of gene coexpression data in animals. For this purpose, we implemented a new comparable coexpression measure, Mutual Rank, included five other animal species, rat, chicken, zebrafish, fly and nematoda, to assess the conservation of coexpression, and added different layers of omics data into the integrated network of genes. Comparison of coexpression is a key concept to enhance the reliability of gene coexpression, and the integration of different information can reduce the noise inherent in the information. With the functions for gene network representation, COXPRESdb can help researchers to clarify the functional and regulatory networks of genes in a broad array of animal species.

Nucleic Acids Res. 2011:39(Database issue) | 51 Citations (from Europe PMC, 2024-04-20)
17932064
COXPRESdb: a database of coexpressed gene networks in mammals. [PMID: 17932064]
Obayashi T, Hayashi S, Shibaoka M, Saeki M, Ohta H, Kinoshita K.

A database of coexpressed gene sets can provide valuable information for a wide variety of experimental designs, such as targeting of genes for functional identification, gene regulation and/or protein-protein interactions. Coexpressed gene databases derived from publicly available GeneChip data are widely used in Arabidopsis research, but platforms that examine coexpression for higher mammals are rather limited. Therefore, we have constructed a new database, COXPRESdb (coexpressed gene database) (http://coxpresdb.hgc.jp), for coexpressed gene lists and networks in human and mouse. Coexpression data could be calculated for 19 777 and 21 036 genes in human and mouse, respectively, by using the GeneChip data in NCBI GEO. COXPRESdb enables analysis of the four types of coexpression networks: (i) highly coexpressed genes for every gene, (ii) genes with the same GO annotation, (iii) genes expressed in the same tissue and (iv) user-defined gene sets. When the networks became too big for the static picture on the web in GO networks or in tissue networks, we used Google Maps API to visualize them interactively. COXPRESdb also provides a view to compare the human and mouse coexpression patterns to estimate the conservation between the two species.

Nucleic Acids Res. 2008:36(Database issue) | 88 Citations (from Europe PMC, 2024-04-20)

Ranking

All databases:
467/6000 (92.233%)
Expression:
73/1143 (93.701%)
Gene genome and annotation:
166/1675 (90.149%)
Interaction:
78/982 (92.159%)
467
Total Rank
365
Citations
22.812
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Record metadata

Created on: 2015-06-20
Curated by:
Xinyu Zhou [2023-09-07]
Dong Zou [2019-01-03]
Dong Zou [2018-03-05]
Mengwei Li [2016-03-31]
Mengwei Li [2015-12-05]
Mengwei Li [2015-06-27]