e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Transcriptome Analysis of the Medulla Tissue from Cattle in Response to Bovine Spongiform Encephalopathy using Digital Gene Expression Tag Profiling


Bovine spongiform encephalopathy (BSE) is a transmissible, fatal neurodegenerative disorder of cattle produced by prions. The use of excessive parallel sequencing for comparison of gene expression in bovine control and infected tissues may help to elucidate the molecular mechanisms associated with this disease. In this study, tag profiling Solexa sequencing was used for transcriptome analysis of bovine brain tissues. Replicate libraries were prepared from mRNA isolated from control and infected (challenged with 100 g of BSE-infected brain) medulla tissues 45 mo after infection. For each library, 5-6 million sequence reads were generated and approximately 67-70% of the reads were mapped against the Bovine Genome database to approximately 13,700-14,120 transcripts (each having at least one read). About 42-47% of the total reads mapped uniquely. Using the GeneSifter software package, 190 differentially expressed (DE) genes were identified (> 2.0-fold change, p < .01): 73 upregulated and 117 downregulated. Seventy-nine DE genes had functions described in the Gene Ontology (GO) database and 16 DE genes were involved in 38 different pathways described in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Digital analysis expression by tag profiling may be a powerful approach to comprehensive transcriptome analysis to identify changes associated with disease progression, leading to a better understanding of the underlying mechanism of pathogenesis of BSE.

  • CA
  • US
  • Univ_Alberta (CA)
Data keywords
  • ontology
Agriculture keywords
  • cattle
Data topic
  • big data
  • information systems
  • semantics
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Univ_Alberta (CA)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.