BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

Background: Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description: BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions: BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License

Functional site prediction selects correct protein models

<p>Abstract</p> <p>Background</p> <p>The prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely to be part of a functional site and this information can be used to select model structures from a variety of alternatives that would correspond to a functional protein.</p> <p>Results</p> <p>Using a large collection of protein-like decoy models, a score was devised that selected those with predicted functional site residues that formed a cluster. When tested on a variety of small <it>α</it>/<it>β</it>/<it>α </it>type proteins, including enzymes and non-enzymes, those that corresponded to the native fold were ranked highly. This performance held also for a selection of larger <it>α</it>/<it>β</it>/<it>α </it>proteins that played no part in the development of the method.</p> <p>Conclusion</p> <p>The use of predicted site positions provides a useful filter to discriminate native-like protein models from non-native models. The method can be applied to any collection of models and should provide a useful aid to all modelling methods from <it>ab initio </it>to homology based approaches.</p

Best practices to maximize the use and reuse of quantitative and systems pharmacology models: recommendations from the United Kingdom quantitative and systems pharmacology network

The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment

BioModels: ten-year anniversary

BioModels (http://www.ebi.ac.uk/biomodels/) is a repository of mathematical models of biological processes. A large set of models is curated to verify both correspondence to the biological process that the model seeks to represent, and reproducibility of the simulation results as described in the corresponding peer-reviewed publication. Many models submitted to the database are annotated, cross-referencing its components to external resources such as database records, and terms from controlled vocabularies and ontologies. BioModels comprises two main branches: one is composed of models derived from literature, while the second is generated through automated processes. BioModels currently hosts over 1200 models derived directly from the literature, as well as in excess of 140 000 models automatically generated from pathway resources. This represents an approximate 60-fold growth for literature-based model numbers alone, since BioModels’ first release a decade ago. This article describes updates to the resource over this period, which include changes to the user interface, the annotation profiles of models in the curation pipeline, major infrastructure changes, ability to perform online simulations and the availability of model content in Linked Data form. We also outline planned improvements to cope with a diverse array of new challenges

Minimum Information About a Simulation Experiment (MIASE)

The original publication is available at www.ploscompbiol.orgReproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes.The discussions that led to the definition of MIASE benefited from the support of a Japan Partnering Award by the UK Biotechnology and Biological Sciences Research Council. DW was supported by the Marie Curie program and by the German Research Association (DFG Research Training School ‘‘dIEM oSiRiS’’ 1387/1). This publication is based on work (EJC) supported in part by Award No KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). FTB acknowledges support by the NIH (grant 1R01GM081070- 01). JC is supported by the European Commission, DG Information Society, through the Seventh Framework Programme of Information and Communication Technologies, under the VPH NoE project (grant number 223920). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Publishers versio

Toward community standards and software for whole-cell modeling

Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate, comprehensive models of complex cells. Methods: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in SBML. Results: Our analysis revealed several challenges to representing WC models using the current standards. Conclusion: We, therefore, propose several new WC modeling standards, software, and databases. Significance:We anticipate that these new standards and software will enable more comprehensive models

Comparison of Image Quality Criteria between Digital Storage Phosphor Plate in Mammography and Full-Field Digital Mammography in the Detection of Breast Cancer

Background: Digital mammography is slowly replacing screen film mammography. In digital mammography, 2 methods are available in acquiring images: digital storage phosphor plate and full-field digital mammography. The aim of this study was to compare the image quality acquired from the 2 methods of digital mammography in the detection of breast cancer. Methods: The study took place at the National Cancer Society, Kuala Lumpur, and followed 150 asymptomatic women for the duration of 1 year. Participating women gave informed consent and were exposed to 4 views from each system. Two radiologists independently evaluated the printed images based on the image quality criteria in mammography. McNemar’s test was used to compare the image quality criteria between the systems. Results: The agreement between the radiologists for the digital storage phosphor plate was ĸ = 0.551 and for full-field digital mammography was, ĸ = 0.523. Full-field digital mammography was significantly better compared with the digital storage phosphor plate in right and left mediolateral oblique views (P < 0.05) in the detection of microcalcifications, which are early signs of breast cancer. However, both systems were comparable in all other aspects of image quality. Conclusion: Digital mammography is a useful screening tool for the detection of early breast cancer and ensures better prognosis and quality of life

Curation and annotation for BioModels Database, a resource of published quantitative kinetic models

BioModels Database (&#x22;http://www.ebi.ac.uk/biomodels/&#x22;:http://www.ebi.ac.uk/biomodels/) is a free resource for storing, viewing and retrieving published, peer-reviewed, quantitative models of biochemical and cellular systems. As a storage format, BioModels Database uses the Systems Biology Markup Language (SBML), but also allows submission and export of models in various other commonly used formats.&#xd;&#xa;&#xd;&#xa;To offer scientists reliable information, models are curated to comply with the MIRIAM (Minimal Information Requested In the Annotation of biochemical Models) standard. This curation process involves verification of the model structure, the parameter and variable values and its mathematical relations. Furthermore reproduction of results in the reference publication is checked.&#xd;&#xa;&#xd;&#xa;The different elements of the models are extensively annotated with references to controlled vocabularies and links to other databases, to allow for identification and search. Those references and links are provided in the exported SBML files as a URN (Uniform Resource Name), identifying the data-type and the data-set, and a qualifier, indicating the relation between the element and the referenced data-set. The URNs follow the MIRIAM scheme and are resolved, for instance to URLs, using the Web Services of MIRIAM Resources (&#x22;http://www.ebi.ac.uk/miriam/&#x22;:http://www.ebi.ac.uk/miriam/)