The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Similarity of gene expression across a wide range of biological conditions can be efficiently used in characterization of gene function. We have constructed a rice gene coexpression database, RiceFREND (http://ricefrend.dna.affrc.go.jp/), to identify gene modules with similar expression profiles and provide a platform for more accurate prediction of gene functions. Coexpression analysis of 27 201 genes was performed against 815 microarray data derived from expression profiling of various organs and tissues at different developmental stages, mature organs throughout the growth from transplanting until harvesting in the field and plant hormone treatment conditions, using a single microarray platform. The database is provided with two search options, namely, 'single guide gene search' and 'multiple guide gene search' to efficiently retrieve information on coexpressed genes. A user-friendly web interface facilitates visualization and interpretation of gene coexpression networks in HyperTree, Cytoscape Web and Graphviz formats. In addition, analysis tools for identification of enriched Gene Ontology terms and cis-elements provide clue for better prediction of biological functions associated with the coexpressed genes. These features allow users to clarify gene functions and gene regulatory networks that could lead to a more thorough understanding of many complex agronomic traits.
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