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Cooper, L.

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Cooper
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Cooper, L.
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0000-0002-6379-8932

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    The Ontologies Community of Practice: a CGIAR initiative for big data in agrifood systems
    (Cell Press, 2020) Arnaud, E.; Laporte, M.A.; Soonho Kim; Aubert, C.; Leonelli, S.; Miro, B.; Cooper, L.; Jaiswal, P.; Kruseman, G.; Shrestha, R.; Buttigieg, P.L.; Mungall, C.; Pietragalla, J.; Agbona, A.; Muliro, J.; Detras, J.; Hualla, V.; Abhishek Rathore; Das, R.R.; Dieng, I.; Bauchet, G.J.; Menda, N.; Pommier, C.; Shaw, F.; Lyon, D.A.; Mwanzia, L.; Juarez, H.; Bonaiuti, E.; Chiputwa, B.; Obileye, O.; Auzoux, S.; Dzale Yeumo, E.; Mueller, L.A.; Silverstein, K.; Lafargue, A.; Antezana, E.; Devare, M.; King, B.
    Publication
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    Developing data interoperability using standards: a wheat community use case
    (F1000 Research, 2017) Dzale Yeumo, E.; Alaux, M.; Arnaud, E.; Aubin, S.; Baumann, U.; Buche, P.; Cooper, L.; Cwiek-Kupczynska, H.; Davey, R.; Fulss, R.; Jonquet, C.; Laporte, M.A.; Larmande, P.; Pommier, C.; Protonotarios, V.; Reverté, C.; Shrestha, R.; Subirats, I.; Venkatesan, A.; Whan, A.; Quesneville, H.
    In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach’s potential to be generalizable to other (agricultural) domains.
    Publication
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    The plant ontology as a tool for comparative plant anatomy and genomic analyses
    (Oxford University Press, 2012) Cooper, L.; Walls, R.L.; Elser, J.; Gandolfo, M.; Stevenson, D.W.; Smith, B.; Preece, J.; Athreya, B.; Mungall, C.; Rensing, S.; Hiss, M.; Lang, D.; Reski, R.; Berardini, T.; Donghui Li; Huala, E.; Schaeffer, M.; Menda, N.; Arnaud, E.; Shrestha, R.; Yukiko Yamazaki; Jaiswal, P.
    The Plant Ontology (PO; http://www.plantontology.org/) is a publicly-available, collaborative effort to develop and maintain a controlled, structured vocabulary (?ontology?) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multi-species anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontology that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to over 110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and Quantitative Traits Loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users, and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs.
    Publication