Yannick Haudry, C. Ong, L. Ettwiller, Hugo Bérubé, Ivica Letunic, M. Kapushesky, Paul-Daniel Weeber, Xi Wang, J. Gagneur, Charles Girardot, D. Arendt, P. Bork, A. Brazma, E. Furlong, J. Wittbrodt, T. Henrich
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For this purpose we have integrated gene expression data for zebrafish, medaka, drosophila and mouse into a central public repository named 4DXpress (http://ani.embl.de/4DXpress). 4DXpress allows to query anatomy ontology based expression annotations across species and quickly jump from one gene to the orthologs in other species based on ensembl-compara relationships. We have set up a linked resource for microarray data at ArrayExpress. In addition we have mapped developmental stages between the species to be able to compare corresponding developmental time phases. We have used clustering algorithms to classify genes based on their expression pattern annotations. To illustrate the use of 4DXpress we systematically analysed the relationships between conserved regulatory inputs and spatio-temporal gene expression derived from 4DXpress and found significant correlation between expression patterns of genes predicted to have similar regulatory elements in their promoters.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"62 1","pages":"373-382"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparing and Analysing Gene Expression Patterns Across Animal Species Using 4DXpress\",\"authors\":\"Yannick Haudry, C. Ong, L. Ettwiller, Hugo Bérubé, Ivica Letunic, M. Kapushesky, Paul-Daniel Weeber, Xi Wang, J. Gagneur, Charles Girardot, D. Arendt, P. Bork, A. Brazma, E. Furlong, J. Wittbrodt, T. Henrich\",\"doi\":\"10.1142/9781848161092_0038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-resolution spatial information on gene expression over time can be acquired through whole mount in-situ hybridisation experiments in animal model species such as fish, fly or mouse. Expression patterns of many genes have been studied and data has been integrated into dedicated model organism databases like ZFIN for zebrafish, MEPD for medaka, BDGP for drosophila or MGI for mouse. Nevertheless, a central repository that allows users to query and compare gene expression patterns across different species has not yet been established. For this purpose we have integrated gene expression data for zebrafish, medaka, drosophila and mouse into a central public repository named 4DXpress (http://ani.embl.de/4DXpress). 4DXpress allows to query anatomy ontology based expression annotations across species and quickly jump from one gene to the orthologs in other species based on ensembl-compara relationships. We have set up a linked resource for microarray data at ArrayExpress. In addition we have mapped developmental stages between the species to be able to compare corresponding developmental time phases. We have used clustering algorithms to classify genes based on their expression pattern annotations. 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Comparing and Analysing Gene Expression Patterns Across Animal Species Using 4DXpress
High-resolution spatial information on gene expression over time can be acquired through whole mount in-situ hybridisation experiments in animal model species such as fish, fly or mouse. Expression patterns of many genes have been studied and data has been integrated into dedicated model organism databases like ZFIN for zebrafish, MEPD for medaka, BDGP for drosophila or MGI for mouse. Nevertheless, a central repository that allows users to query and compare gene expression patterns across different species has not yet been established. For this purpose we have integrated gene expression data for zebrafish, medaka, drosophila and mouse into a central public repository named 4DXpress (http://ani.embl.de/4DXpress). 4DXpress allows to query anatomy ontology based expression annotations across species and quickly jump from one gene to the orthologs in other species based on ensembl-compara relationships. We have set up a linked resource for microarray data at ArrayExpress. In addition we have mapped developmental stages between the species to be able to compare corresponding developmental time phases. We have used clustering algorithms to classify genes based on their expression pattern annotations. To illustrate the use of 4DXpress we systematically analysed the relationships between conserved regulatory inputs and spatio-temporal gene expression derived from 4DXpress and found significant correlation between expression patterns of genes predicted to have similar regulatory elements in their promoters.