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Orymold: ontology based gene expression data integration and analysis tool applied to rice.

Mercadé J, Espinosa A, Adsuara JE, Adrados R, Segura J, Maes T - BMC Bioinformatics (2009)

Bottom Line: The software provides tools to use the semantic model to postulate and validate of hypotheses on the spatial and temporal expression and function of genes.In order to illustrate the software's use and features, we used it to build a semantic model of rice (Oryza sativa) and integrated experimental data into it.In this paper we describe the development and features of a flexible software application for dynamic gene expression data annotation, integration, and exploration called Orymold.

View Article: PubMed Central - HTML - PubMed

Affiliation: Oryzon Genomics, Parc Científic de Barcelona, 08028 Barcelona, Spain. jmercade@oryzon.com

ABSTRACT

Background: Integration and exploration of data obtained from genome wide monitoring technologies has become a major challenge for many bioinformaticists and biologists due to its heterogeneity and high dimensionality. A widely accepted approach to solve these issues has been the creation and use of controlled vocabularies (ontologies). Ontologies allow for the formalization of domain knowledge, which in turn enables generalization in the creation of querying interfaces as well as in the integration of heterogeneous data, providing both human and machine readable interfaces.

Results: We designed and implemented a software tool that allows investigators to create their own semantic model of an organism and to use it to dynamically integrate expression data obtained from DNA microarrays and other probe based technologies. The software provides tools to use the semantic model to postulate and validate of hypotheses on the spatial and temporal expression and function of genes. In order to illustrate the software's use and features, we used it to build a semantic model of rice (Oryza sativa) and integrated experimental data into it.

Conclusion: In this paper we describe the development and features of a flexible software application for dynamic gene expression data annotation, integration, and exploration called Orymold. Orymold is freely available for non-commercial users from http://www.oryzon.com/media/orymold.html.

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Orymold interfaces. Upper image shows the main interface of the application, with the customizable ontology on the upper left part, the atlas on the upper right, and the working lists at the bottom. The inner integument region of the ovule on the atlas picture appears highlighted as a result of sliding the mouse pointer over it, allowing for a fast and visual identification of each region. Bottom image shows the basic interface for retrieving MA data from a selected region. Users are able to browse experiments and its contained data. In the background, the atlas feature shows a section of an anther.
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Figure 4: Orymold interfaces. Upper image shows the main interface of the application, with the customizable ontology on the upper left part, the atlas on the upper right, and the working lists at the bottom. The inner integument region of the ovule on the atlas picture appears highlighted as a result of sliding the mouse pointer over it, allowing for a fast and visual identification of each region. Bottom image shows the basic interface for retrieving MA data from a selected region. Users are able to browse experiments and its contained data. In the background, the atlas feature shows a section of an anther.

Mentions: Single probe data insertion involves the mapping of a single probe sequence to a sequence present in the OryDB database, as well as the insertion of the experimental picture where the expression of the targeted mRNA is evidenced. Since the experimental picture will probably show expression of the probe target for more than a single term in the ontology, the probe will have to be introduced in the higher term in the hierarchy represented in the picture. By selecting such term in the ontology and selecting "insert data" in the contextual menu, a pop-up interface will appear, allowing the investigator to upload and define the data to insert (see Fig. 4). The insertion interface allows for the relation of a probe sequence in FASTA format with an experimental picture. All child terms of the term where the investigator has chosen to insert data are listed to provide the quantification of the expression detected by the probe for each of them. The qualification will be based in the visual interpretation of the experimental picture by the researcher-curator in a discrete range from zero to four. Since it is possible that a listed term will not appear in the picture or be unclear as to whether there is expression or not for a given region, a "N/A" qualification is allowed for the term to indicate that there is no conclusive evidence for expression or for non-expression. Along with the probe sequence, the expression values for all terms, and the experimental picture, an atlas based composition will be created and stored according to the expression values. Using the parent term to retrieve the main picture and the coloured maps of the regions set as having expression (one to four in the discrete range) by the curator, a composition will be automatically created and stored at insertion time, taking full advantage of the atlas feature. Thus, the system will be storing two visual resources of the experiment: the original picture of the experiment and the fully atlas integrated representation of the expression as interpreted by the curator.


Orymold: ontology based gene expression data integration and analysis tool applied to rice.

Mercadé J, Espinosa A, Adsuara JE, Adrados R, Segura J, Maes T - BMC Bioinformatics (2009)

Orymold interfaces. Upper image shows the main interface of the application, with the customizable ontology on the upper left part, the atlas on the upper right, and the working lists at the bottom. The inner integument region of the ovule on the atlas picture appears highlighted as a result of sliding the mouse pointer over it, allowing for a fast and visual identification of each region. Bottom image shows the basic interface for retrieving MA data from a selected region. Users are able to browse experiments and its contained data. In the background, the atlas feature shows a section of an anther.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2696451&req=5

Figure 4: Orymold interfaces. Upper image shows the main interface of the application, with the customizable ontology on the upper left part, the atlas on the upper right, and the working lists at the bottom. The inner integument region of the ovule on the atlas picture appears highlighted as a result of sliding the mouse pointer over it, allowing for a fast and visual identification of each region. Bottom image shows the basic interface for retrieving MA data from a selected region. Users are able to browse experiments and its contained data. In the background, the atlas feature shows a section of an anther.
Mentions: Single probe data insertion involves the mapping of a single probe sequence to a sequence present in the OryDB database, as well as the insertion of the experimental picture where the expression of the targeted mRNA is evidenced. Since the experimental picture will probably show expression of the probe target for more than a single term in the ontology, the probe will have to be introduced in the higher term in the hierarchy represented in the picture. By selecting such term in the ontology and selecting "insert data" in the contextual menu, a pop-up interface will appear, allowing the investigator to upload and define the data to insert (see Fig. 4). The insertion interface allows for the relation of a probe sequence in FASTA format with an experimental picture. All child terms of the term where the investigator has chosen to insert data are listed to provide the quantification of the expression detected by the probe for each of them. The qualification will be based in the visual interpretation of the experimental picture by the researcher-curator in a discrete range from zero to four. Since it is possible that a listed term will not appear in the picture or be unclear as to whether there is expression or not for a given region, a "N/A" qualification is allowed for the term to indicate that there is no conclusive evidence for expression or for non-expression. Along with the probe sequence, the expression values for all terms, and the experimental picture, an atlas based composition will be created and stored according to the expression values. Using the parent term to retrieve the main picture and the coloured maps of the regions set as having expression (one to four in the discrete range) by the curator, a composition will be automatically created and stored at insertion time, taking full advantage of the atlas feature. Thus, the system will be storing two visual resources of the experiment: the original picture of the experiment and the fully atlas integrated representation of the expression as interpreted by the curator.

Bottom Line: The software provides tools to use the semantic model to postulate and validate of hypotheses on the spatial and temporal expression and function of genes.In order to illustrate the software's use and features, we used it to build a semantic model of rice (Oryza sativa) and integrated experimental data into it.In this paper we describe the development and features of a flexible software application for dynamic gene expression data annotation, integration, and exploration called Orymold.

View Article: PubMed Central - HTML - PubMed

Affiliation: Oryzon Genomics, Parc Científic de Barcelona, 08028 Barcelona, Spain. jmercade@oryzon.com

ABSTRACT

Background: Integration and exploration of data obtained from genome wide monitoring technologies has become a major challenge for many bioinformaticists and biologists due to its heterogeneity and high dimensionality. A widely accepted approach to solve these issues has been the creation and use of controlled vocabularies (ontologies). Ontologies allow for the formalization of domain knowledge, which in turn enables generalization in the creation of querying interfaces as well as in the integration of heterogeneous data, providing both human and machine readable interfaces.

Results: We designed and implemented a software tool that allows investigators to create their own semantic model of an organism and to use it to dynamically integrate expression data obtained from DNA microarrays and other probe based technologies. The software provides tools to use the semantic model to postulate and validate of hypotheses on the spatial and temporal expression and function of genes. In order to illustrate the software's use and features, we used it to build a semantic model of rice (Oryza sativa) and integrated experimental data into it.

Conclusion: In this paper we describe the development and features of a flexible software application for dynamic gene expression data annotation, integration, and exploration called Orymold. Orymold is freely available for non-commercial users from http://www.oryzon.com/media/orymold.html.

Show MeSH