Browsing by Author "Stanford, Natalie J."

Now showing 1 - 4 of 4
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    The evolution of standards and data management practices in systems biology
    (EMBO, 2015-12) Stanford, Natalie J.; Wolstencroft, Katherine; Golebiewski, Martin; Kania, Renate; Juty, Nick; Tomlinson, Christopher; Owen, Stuart; Butcher, Sarah; Hermjakob, Henning; Le Novere, Nicolas; Mueller, Wolfgang; Snoep, Jacky; Goble, Carole
    Systems biology involves the integration of multiple heterogeneous data sets, in order to model and predict biological processes. The domain's interdisciplinary nature requires data, models and other research assets to be formatted and described in standard ways to enable exchange and reuse. Infrastructure for Systems Biology Europe (ISBE) is a project to establish essential, centralized services for systems biology researchers throughout the systems biology lifecycle. A key component of ISBE is to support the management, integration and exchange of data, models, results and protocols. To inform further ISBE development, we surveyed the community to evaluate the uptake of available standards, and current practices of researchers in data and model management.
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    FAIRDOMHub : a repository and collaboration environment for sharing systems biology research
    (Oxford University Press on behalf of Nucleic Acids Research, 2017) Wolstencroft, Katherine; Krebs, Olga; Snoep, Jacky L.; Stanford, Natalie J.; Bacall, Finn; Golebiewski, Martin; Kuzyakiv, Rostyk; Nguyen, Quyen; Owen, Stuart; Soiland-Reyes, Stian; Straszewski, Jakub; Van Niekerk, David D.; Williams, Alan R.; Malmstrom, Lars; Rinn, Bernd; Muller, Wolfgang; Goble, Carole
    The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.
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    Identifiers for the 21st century : how to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data
    (Public Library of Science, 2017-06-29) McMurry, Julie A.; Juty, Nick; Blomberg, Niklas; Burdett, Tony; Conlin, Tom; Conte, Nathalie; Courtot, Melanie; Deck, John; Dumontier, Michel; Fellows, Donal K.; Gonzalez-Beltran, Alejandra; Gormanns, Philipp; Grethe, Jeffrey; Hastings, Janna; Heriche, Jean-Karim; Hermjakob, Henning; Ison, Jon C.; Jimenez, Rafael C.; Jupp, Simon; Kunze, John; Laibe, Camille; Le Novere, Nicolas; Malone, James; Martin, Maria Jesus; McEntyre, Johanna R.; Morris, Chris; Muilu, Juha; Muller, Wolfgang; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Sariyar, Murat; Snoep, Jacky L.; Soiland-Reyes, Stian; Stanford, Natalie J.; Swainston, Neil; Washington, Nicole; Williams, Alan R.; Wimalaratne, Sarala M.; Winfree, Lilly M.; Wolstencroft, Katherine; Goble, Carole; Mungall, Christopher J.; Haende, Melissa A.; Parkinson, Helen
    In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.
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    SEEK : a systems biology data and model management platform
    (BioMed Central, 2015-07-11) Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J.; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L.; Mueller, Wolfgang; Goble, Carole
    Background: Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. Results: The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. Conclusion: The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.