http://precedings.nature.com/tags/standards Recently posted documents tagged with 'standards' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3145.1 See also related posterToday’s researchers can perform biological and biomedical studies where the same material is run through a wide range of assays, comprising several technologies such as genomics, transcriptomics, proteomics and metabol/nomics (hereafter referred as ‘omics’). To enable others to correctly interpret the complex data sets that result, and the conclusions drawn, it is necessary to provide contextualizing experimental metadata at an appropriate level of granularity.Standards initiatives normally cater to particular domains. However, several synergistic standards activities foster cross-domain harmonization of the three kinds of reporting standard (minimum information checklists, ontologies and file formats). Some 29 groups participate in the MIBBI project, which offers a one-stop shop for those exploring the range of extant ‘minimum information’ checklists, and which fosters integrative development1. More than 60 groups participate in the OBO Foundry 2, which coordinates the orthogonal development of ontologies such as OBI for describing experimental (meta)data. And several groups participate in the development of ISA-Tab, a tabular framework for presenting experimental metadata3 (analogous to FuGE, a generic data model to underpin various XML file formats4).We have developed an infrastructure that leverages the aforementioned synergistic reporting standards to create a common structured representation and storage mechanism for experimental metadata from biological and biomedical investigations ranging from simple single-assay studies to complex, methodologically diverse multi-assay studies. View the public instance of our ISA-based infrastructure, running at EBI, and/or download the components for your local use.References1. Taylor CF, Field D, Sansone SA,… Rocca-Serra P et al. (2008) The MIBBI Project. Nature Biotechnology Aug;26(8):889-896. http://www.mibbi.org2. Smith B, Ashburner M, Rosse C,… Rocca-Serra P, …Sansone SA et al. (2007) The OBO Foundry. Nature Biotechnology Nov;25(11):1251-5. http://www.obofoundry.org3. Sansone SA, Rocca-Serra P, Brandizi M,… Taylor CF et al. (2008) The First MGED RSBI (ISA-TAB) Workshop. OMICS. Jun;12(2):143-9. http://isatab.sf.net4. Jones AR, Miller M, Aebersold R,… Sansone SA et al. (2007) The Functional Genomics Experiment model (FuGE). Nature Biotechnology Oct;25(10):1127-1133. http://fuge.sf.net http://dx.doi.org/10.1038/npre.2009.3145.1 Wed, 22 Apr 2009 21:18:50 UTC Standards and infrastructure for managing experimental metadata doi:10.1038/npre.2009.3145.1 2009-04-23 Susanna-Assunta Sansone Nature Precedings 2009-04-22T21:18:50Z Presentation Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3144.1 See also the related presentationWe present an infrastructure that leverages synergistic reporting standards and ontologies1,2,3,4,5 to create a common structured representation and storage mechanism for experimental metadata from biological and biomedical investigations ranging from simple single-assay studies to complex, methodologically diverse multi-assay studies. The infrastructure’s components include: a data capture and editing tool (ISAcreator); validator (ISAvalidator); database (BioInvestigation Index); and converter (ISAconverter); and a BioConductor analysis package (R-ISApackage). The components are designed for local installation, and can work independently, or as unified system.View the public instance running at EBI and/or download the components for your local use.References1. Taylor CF, Field D, Sansone SA,… Rocca-Serra P et al. (2008) The MIBBI Project. Nature Biotechnology Aug;26(8):889-896. http://www.mibbi.org2. Smith B, Ashburner M, Rosse C,… Rocca-Serra P, …Sansone SA et al. (2007) The OBO Foundry. Nature Biotechnology Nov;25(11):1251-5. http://www.obofoundry.org3. Ontology for Biomedical Investigations (OBI) http://obi-ontology.org 4. Sansone SA, Rocca-Serra P, Brandizi M,… Taylor CF et al. (2008) The First MGED RSBI (ISA-TAB) Workshop. OMICS. Jun;12(2):143-9. http://isatab.sf.net5. Jones AR, Miller M, Aebersold R,… Sansone SA et al. (2007) The Functional Genomics Experiment model (FuGE). Nature Biotechnology Oct;25(10):1127-1133. http://fuge.sf.net http://dx.doi.org/10.1038/npre.2009.3144.1 Wed, 22 Apr 2009 21:18:37 UTC Standards and infrastructure for managing experimental metadata doi:10.1038/npre.2009.3144.1 2009-04-23 Susanna-Assunta Sansone Nature Precedings 2009-04-22T21:18:37Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1720/version/2 This module represents the formalised opinion of the authors and the CARMEN consortium, which identifies the minimum information required to report the use of electrophysiology in a neuroscience study, for submissionto the CARMEN system (www.carmen.org.uk). http://precedings.nature.com/documents/1720/version/2 Thu, 09 Apr 2009 14:45:14 UTC Minimum Information about a Neuroscience Investigation (MINI): Electrophysiology hdl:10101/npre.2009.1720.2 2009-04-09 Frank Gibson Nature Precedings 2009-04-09T14:45:14Z Manuscript Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1720/version/1 This module represents the formalized opinion of the authors and the CARMEN consortium, which identifies the minimum information required to report the use of electrophysiology in a neuroscience study, for submission to the CARMEN system (www.carmen.org.uk). http://precedings.nature.com/documents/1720/version/1 Tue, 25 Mar 2008 18:21:55 UTC Minimum Information about a Neuroscience Investigation (MINI) Electrophysiology hdl:10101/npre.2008.1720.1 2008-03-25 Frank Gibson Nature Precedings 2008-03-25T18:21:55Z Manuscript Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2007.21.1 A cornerstone of systems biology is the use of computational modeling, by which hypotheses can be cast into a quantitative form that can be tested systematically. The use of computational modeling by biologists promises to pave the way for more rigorous analyses of biological functions, and ultimately will lead to new and better treatments for disease.A crucial enabler for more widespread use of computational modeling in biology is reaching agreement on how to represent, store, and communicate models between software tools. The Systems Biology Markup Language (SBML) project is an effort to create a machine-readable format for representing computational models in biology. By supporting SBML as an input and output format, different software tools can operate on the same representation of a model, removing chances for errors in translation and assuring a common starting point for analyses and simulations. SBML has become the most successful effort in this direction so far, with over 100 software systems supporting it today.In this presentation, I will discuss the current state of SBML, including recent developments such as this year’s finalization of Version 2 of SBML Level 2. I will also survey some of the software tools that support SBML, and related projects that have arisen to support more effective use of computational models. Lastly, I will discuss expected future developments in SBML. http://dx.doi.org/10.1038/npre.2007.21.1 Mon, 22 Jan 2007 01:52:11 UTC The Systems Biology Markup Language (SBML): Where It’s Been and Where It’s Going doi:10.1038/npre.2007.21.1 2007-01-22 Michael Hucka Nature Precedings 2007-01-22T01:52:11Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2007.20.1 Systems biology has arisen through the convergence of theoretical, computational, and mathematical modeling of systems and the need to understand the wealth of information being rapidly generated in biology. Systems biology by its nature requires collaborations between scientists with expertise in biology, chemistry, computer sciences, engineering, mathematics, and physics. Successful integration of these disciplines depends on bringing to bear both social and technological tools: namely, consortia that help forge collaborations and common understanding, software tools that permit analysis of vast and complex data, and agreed-upon standards that enable researchers to communicate and reuse each other’s results in practical and unambiguous ways. In this presentation, I will discuss several international projects (SBML, SBGN, and BioModels.net) aimed at addressing the last issue.An important prerequisite for effective sharing of computational models is reaching agreement on how to communicate them, both between software and between humans. The Systems Biology Markup Language (SBML) project is an effort to create a machine-readable format for representing computational models at the biochemical reaction level. By supporting SBML as an input and output format, different software tools can operate on the same representation of a model, removing chance for errors in translation and assuring a common starting point for analyses and simulations. SBML has become the most successful effort in this direction so far, with nearly 100 software tools supporting it today.A recently-created sister project is the Systems Biology Graphical Notation (SBGN) project. It addresses the issue of consistent human communication, by attempting to add more rigor and consistency to the graphical network diagrams that often accompany published research on models of biological reaction systems. The real payoff will come when more people and software adopt such a common visual notation and it becomes as familiar to them as circuit schematics are to electronics engineers.Finally, when developing and publishing computational models, it is only natural to want to put them into a database. The BioModels.net project is an effort to (1) provide a free, centralized, publicly-accessible database of human-curated computational models in SBML and other structured formats; (2) define agreed-upon standards for model curation; and (2) define agreed-upon vocabularies for annotating models with connections to biological data resources. http://dx.doi.org/10.1038/npre.2007.20.1 Mon, 22 Jan 2007 01:50:17 UTC Evolving standards and infrastructure for systems biology: SBML, SBGN, and BioModels.net doi:10.1038/npre.2007.20.1 2007-01-22 Michael Hucka Nature Precedings 2007-01-22T01:50:17Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2007.19.1 The Systems Biology Markup Language (SBML) is a machine-readable model representation language for software tools in computational systems biology. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. SBML is by no means a perfect format, but it has achieved widespread acceptance as a de facto standard. It is supported worldwide by over 100 software systems (both open-source and commercial). The broad acceptance of a common, open format for exchanging models between software tools is a crucial step towards wider use of quantitative modeling in biology, because it allows researchers to build upon each other’s work with greater ease and accuracy.SBML can encode models consisting of biochemical entities (species) linked by reactions to form networks. An important principle is that models are decomposed into explicitly-labeled constituent elements, the set of which resembles a verbose rendition of chemical reaction equations. The representation deliberately does not cast the model directly into a set of differential equations or other specific interpretation of the model. The formalisms in SBML allows a wide range of biological phenomena to be modeled, including metabolism, cell signaling, gene regulation, and more. Significant flexibility and power comes from the ability to define arbitrary formulae for the rates of change of variables as well as the ability to express other constraints mathematically.This tutorial covered the latest edition of SBML, which is Level 2 Version 2, finalized in September 2006. Topics covered include the basic common principles in SBML as well the changes introduced in Level 2 Version 2. We also discussed software tools for programmers, in particular libSBML. http://dx.doi.org/10.1038/npre.2007.19.1 Mon, 22 Jan 2007 01:48:17 UTC The Systems Biology Markup Language (SBML) Level 2 Version 2 doi:10.1038/npre.2007.19.1 2007-01-22 Michael Hucka Nature Precedings 2007-01-22T01:48:17Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2006.10.1 The practise of Systems Biology relies on interfaces. Interfacesbetween the entities we study: the paradigm moved from a physicalobject centric view toward a relationship-centric one; interfacesbetween tools: From the retrieval of the primary data to the fineanalysis of a model’s behaviour, one uses many tools, more or lesswell connected; interfaces between individuals: To build anynon-trivial mechanistic model requires to merge existing work andgather external expertise.If we want these interfaces to be generic enough to allow for anybodyto leverage on existing toolkits, a fundamental requirement is theexistence of community-developed well supported standards, but alsoopen resources where to find the “lego” blocks. Over the lasthalf-decade, several efforts have been launched in that direction,whether concerning encoding format, ontologies or databases. Some ofthem are now well-established in the field and play a significant roleto improve its coherence but also to increase the size and the qualityof quantitative models. http://dx.doi.org/10.1038/npre.2006.10.1 Thu, 30 Nov 2006 15:13:38 UTC Open Standards and Resources in Systems Biology: collaborative scale-up toward virtual life doi:10.1038/npre.2006.10.1 2006-11-30 Nicolas Le Novere Nature Precedings 2006-11-30T15:13:38Z Presentation Biotechnology http://creativecommons.org/licenses/by/2.5/