MaSyMoS is a tool for finding hidden treasures in model repositories by enabling semantic searches across models, annotations, and associated data. It addresses a common problem researchers face in difficulty managing and accessing their data. MaSyMoS allows users to query model repositories to find models associated with certain publications, genes, or behaviors. It also provides files needed to run simulations from retrieved models. The tool aims to help researchers better discover, organize, and leverage existing computational models.
A presentation on annotations for computational biological models. Second part is on SED-ML, a format for the storage of simulation experiment descriptions.
This document discusses challenges to reproducibility in systems biology and potential solutions. It notes a lack of data standards, quality, availability, and transparency make it difficult for researchers to reproduce results. Tools and initiatives discussed that aim to improve reproducibility include the COMBINE archive to bundle necessary files, graph databases to integrate model-related data, and version control systems to track model evolution over time. The overall goal is to better support scientists in sharing reproducible model-based studies.
Slides from the presentation at IDAMO 2016, Rostock. May 2016.
Most scientific discoveries rely on previous or other findings. A lack of transparency and openness led to what many consider the "reproducibility crisis" in systems biology and systems medicine. The crisis arose from missing standards and inappropriate support of
standards in software tools. As a consequence, numerous results in low-and high-profile publications cannot be reproduced.
In my presentation, I summarise key challenges of reproducibility in systems biology and systems medicine, and I demonstrate available solutions to the related problems.
Ron Henkel's presentation of our Ranked Retrieval approach; 2012 PALs meeting of the Sysmo-SEEK project in Heidelberg, Germany. 28th-30th of November 2012.
This document discusses SED-ML (Simulation Experiment Description Markup Language), a standard for describing computational simulations. SED-ML files contain information like the models, data, simulation settings and algorithms used in an experiment. Using SED-ML allows experiments to be reproduced and shared. The document encourages adopting SED-ML to make research more reproducible and help curation of models in repositories. It also provides an overview of tools that support SED-ML and ways to get involved in its development.
This document discusses data and model management in systems biology. It covers topics such as data ownership, metadata, ontologies, standards for encoding models and analyses, and tools for working with systems biology models and data. Standards like SBML, SBGN, SED-ML and COMBINE Archive allow for structured representation, visualization, simulation, and sharing of models and data. Resources like SEEK enable curation, simulation and publication of models in a findable, accessible, interoperable and reusable (FAIR) manner.
Strategic Brand Management covers topics such as the history of watchmaking, key figures like Patek Philippe and Adrien Philippe, and the development of Patek Philippe into the premier luxury watch brand known for craftsmanship, heritage, and accomplished individuals. The lecture discusses the brand's values like tradition, excellence in design and manufacturing, and balancing craftsmanship with innovation to produce highly complicated watches and jewelry to this day. Patek Philippe has established itself as one of the most prestigious watch brands in the world through over 175 years of watchmaking expertise, accomplished owners and artisans, and upholding traditions while embracing modern times
MaSyMoS is a tool for finding hidden treasures in model repositories by enabling semantic searches across models, annotations, and associated data. It addresses a common problem researchers face in difficulty managing and accessing their data. MaSyMoS allows users to query model repositories to find models associated with certain publications, genes, or behaviors. It also provides files needed to run simulations from retrieved models. The tool aims to help researchers better discover, organize, and leverage existing computational models.
A presentation on annotations for computational biological models. Second part is on SED-ML, a format for the storage of simulation experiment descriptions.
This document discusses challenges to reproducibility in systems biology and potential solutions. It notes a lack of data standards, quality, availability, and transparency make it difficult for researchers to reproduce results. Tools and initiatives discussed that aim to improve reproducibility include the COMBINE archive to bundle necessary files, graph databases to integrate model-related data, and version control systems to track model evolution over time. The overall goal is to better support scientists in sharing reproducible model-based studies.
Slides from the presentation at IDAMO 2016, Rostock. May 2016.
Most scientific discoveries rely on previous or other findings. A lack of transparency and openness led to what many consider the "reproducibility crisis" in systems biology and systems medicine. The crisis arose from missing standards and inappropriate support of
standards in software tools. As a consequence, numerous results in low-and high-profile publications cannot be reproduced.
In my presentation, I summarise key challenges of reproducibility in systems biology and systems medicine, and I demonstrate available solutions to the related problems.
Ron Henkel's presentation of our Ranked Retrieval approach; 2012 PALs meeting of the Sysmo-SEEK project in Heidelberg, Germany. 28th-30th of November 2012.
This document discusses SED-ML (Simulation Experiment Description Markup Language), a standard for describing computational simulations. SED-ML files contain information like the models, data, simulation settings and algorithms used in an experiment. Using SED-ML allows experiments to be reproduced and shared. The document encourages adopting SED-ML to make research more reproducible and help curation of models in repositories. It also provides an overview of tools that support SED-ML and ways to get involved in its development.
This document discusses data and model management in systems biology. It covers topics such as data ownership, metadata, ontologies, standards for encoding models and analyses, and tools for working with systems biology models and data. Standards like SBML, SBGN, SED-ML and COMBINE Archive allow for structured representation, visualization, simulation, and sharing of models and data. Resources like SEEK enable curation, simulation and publication of models in a findable, accessible, interoperable and reusable (FAIR) manner.
Strategic Brand Management covers topics such as the history of watchmaking, key figures like Patek Philippe and Adrien Philippe, and the development of Patek Philippe into the premier luxury watch brand known for craftsmanship, heritage, and accomplished individuals. The lecture discusses the brand's values like tradition, excellence in design and manufacturing, and balancing craftsmanship with innovation to produce highly complicated watches and jewelry to this day. Patek Philippe has established itself as one of the most prestigious watch brands in the world through over 175 years of watchmaking expertise, accomplished owners and artisans, and upholding traditions while embracing modern times
Introduction to the hands on session on "Standards and tools for model management" at the ICSB 2015.
Focus on COMBINE standards, tools for search, version control and archiving. Used management platform is SEEK.