Literature DB >> 21943917

The SEEK: a platform for sharing data and models in systems biology.

Katy Wolstencroft1, Stuart Owen, Franco du Preez, Olga Krebs, Wolfgang Mueller, Carole Goble, Jacky L Snoep.   

Abstract

Systems biology research is typically performed by multidisciplinary groups of scientists, often in large consortia and in distributed locations. The data generated in these projects tend to be heterogeneous and often involves high-throughput "omics" analyses. Models are developed iteratively from data generated in the projects and from the literature. Consequently, there is a growing requirement for exchanging experimental data, mathematical models, and scientific protocols between consortium members and a necessity to record and share the outcomes of experiments and the links between data and models. The overall output of a research consortium is also a valuable commodity in its own right. The research and associated data and models should eventually be available to the whole community for reuse and future analysis. The SEEK is an open-source, Web-based platform designed for the management and exchange of systems biology data and models. The SEEK was originally developed for the SysMO (systems biology of microorganisms) consortia, but the principles and objectives are applicable to any systems biology project. The SEEK provides an index of consortium resources and acts as gateway to other tools and services commonly used in the community. For example, the model simulation tool, JWS Online, has been integrated into the SEEK, and a plug-in to PubMed allows publications to be linked to supporting data and author profiles in the SEEK. The SEEK is a pragmatic solution to data management which encourages, but does not force, researchers to share and disseminate their data to community standard formats. It provides tools to assist with management and annotation as well as incentives and added value for following these recommendations. Data exchange and reuse rely on sufficient annotation, consistent metadata descriptions, and the use of standard exchange formats for models, data, and the experiments they are derived from. In this chapter, we present the SEEK platform, its functionalities, and the methods employed for lowering the barriers to adoption of standard formats. As the production of biological data continues to grow, in systems biology and in the life sciences in general, the need to record, manage, and exploit this wealth of information in the future is increasing. We promote the SEEK as a data and model management tool that can be adapted to the specific needs of a particular systems biology project.
Copyright © 2011 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21943917     DOI: 10.1016/B978-0-12-385118-5.00029-3

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  13 in total

1.  Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices.

Authors:  Natalie J Stanford; Martin Scharm; Paul D Dobson; Martin Golebiewski; Michael Hucka; Varun B Kothamachu; David Nickerson; Stuart Owen; Jürgen Pahle; Ulrike Wittig; Dagmar Waltemath; Carole Goble; Pedro Mendes; Jacky Snoep
Journal:  Methods Mol Biol       Date:  2019

2.  openBIS: a flexible framework for managing and analyzing complex data in biology research.

Authors:  Angela Bauch; Izabela Adamczyk; Piotr Buczek; Franz-Josef Elmer; Kaloyan Enimanev; Pawel Glyzewski; Manuel Kohler; Tomasz Pylak; Andreas Quandt; Chandrasekhar Ramakrishnan; Christian Beisel; Lars Malmström; Ruedi Aebersold; Bernd Rinn
Journal:  BMC Bioinformatics       Date:  2011-12-08       Impact factor: 3.307

3.  The eGenVar data management system--cataloguing and sharing sensitive data and metadata for the life sciences.

Authors:  Sabry Razick; Rok Močnik; Laurent F Thomas; Einar Ryeng; Finn Drabløs; Pål Sætrom
Journal:  Database (Oxford)       Date:  2014-03-28       Impact factor: 3.451

4.  WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions.

Authors:  Jonathan R Karr; Nolan C Phillips; Markus W Covert
Journal:  Database (Oxford)       Date:  2014-09-16       Impact factor: 3.451

Review 5.  Improving collaboration by standardization efforts in systems biology.

Authors:  Andreas Dräger; Bernhard Ø Palsson
Journal:  Front Bioeng Biotechnol       Date:  2014-12-08

6.  SEEK: a systems biology data and model management platform.

Authors:  Katherine Wolstencroft; Stuart Owen; Olga Krebs; Quyen Nguyen; Natalie J Stanford; Martin Golebiewski; Andreas Weidemann; Meik Bittkowski; Lihua An; David Shockley; Jacky L Snoep; Wolfgang Mueller; Carole Goble
Journal:  BMC Syst Biol       Date:  2015-07-11

Review 7.  Data management strategies for multinational large-scale systems biology projects.

Authors:  Wasco Wruck; Martin Peuker; Christian R A Regenbrecht
Journal:  Brief Bioinform       Date:  2012-10-09       Impact factor: 11.622

8.  A digital repository with an extensible data model for biobanking and genomic analysis management.

Authors:  Massimiliano Izzo; Francesco Mortola; Gabriele Arnulfo; Marco M Fato; Luigi Varesio
Journal:  BMC Genomics       Date:  2014-05-06       Impact factor: 3.969

9.  COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project.

Authors:  Frank T Bergmann; Richard Adams; Stuart Moodie; Jonathan Cooper; Mihai Glont; Martin Golebiewski; Michael Hucka; Camille Laibe; Andrew K Miller; David P Nickerson; Brett G Olivier; Nicolas Rodriguez; Herbert M Sauro; Martin Scharm; Stian Soiland-Reyes; Dagmar Waltemath; Florent Yvon; Nicolas Le Novère
Journal:  BMC Bioinformatics       Date:  2014-12-14       Impact factor: 3.169

Review 10.  A review on computational systems biology of pathogen-host interactions.

Authors:  Saliha Durmuş; Tunahan Çakır; Arzucan Özgür; Reinhard Guthke
Journal:  Front Microbiol       Date:  2015-04-09       Impact factor: 5.640

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.