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1.  Implementing the NICE osteoarthritis guidelines: a mixed methods study and cluster randomised trial of a model osteoarthritis consultation in primary care - the Management of OsteoArthritis In Consultations (MOSAICS) study protocol 
Background
There is as yet no evidence on the feasibility of implementing recommendations from the National Institute of Health and Care Excellence (NICE) osteoarthritis (OA) guidelines in primary care, or of the effect these recommendations have on the condition. The primary aim of this study is to determine the clinical and cost effectiveness of a model OA consultation (MOAC), implementing the core recommendations from the NICE OA guidelines in primary care. Secondary aims are to investigate the impact, feasibility and acceptability of the MOAC intervention; to develop and evaluate a training package for management of OA by general practitioners (GPs) and practice nurses; test the feasibility of deriving ‘quality markers’ of OA management using a new consultation template and medical record review; and describe the uptake of core NICE OA recommendations in participants aged 45 years and over with joint pain.
Design
A mixed methods study with a nested cluster randomised controlled trial.
Method
This study was developed according to a defined theoretical framework (the Whole System Informing Self-management Engagement). An overarching model (the Normalisation Process Theory) will be employed to undertake a comprehensive ‘whole-system’ evaluation of the processes and outcomes of implementing the MOAC intervention. The primary outcome is general physical health (Short Form-12 Physical component score [PCS]) (Ware 1996). The impact, acceptability and feasibility of the MOAC intervention at practice level will be assessed by comparing intervention and control practices using a Quality Indicators template and medical record review. Impact and acceptability of the intervention for patients will be assessed via self-completed outcome measures and semi-structured interviews. The impact, acceptability and feasibility of the MOAC intervention and training for GPs and practice nurses will be evaluated using a variety of methods including questionnaires, semi-structured interviews, and observations.
Discussion
The main output from the study will be to determine whether the MOAC intervention is clinically and cost effective. Additional outputs will be the development of the MOAC for patients consulting with joint pain in primary care, training and educational materials, and resources for patients and professionals regarding supported self-management and uptake of NICE guidance.
Trial registration
ISRCTN number: ISRCTN06984617.
Electronic supplementary material
The online version of this article (doi:10.1186/s13012-014-0095-y) contains supplementary material, which is available to authorized users.
doi:10.1186/s13012-014-0095-y
PMCID: PMC4176866  PMID: 25209897
Osteoarthritis; General practice; Implementation; Primary care; NICE guidelines; Self-management
2.  Controlled vocabularies and semantics in systems biology 
The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. This Perspective discusses the development and use of ontologies that are designed to add semantic information to computational models and simulations.
The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.
doi:10.1038/msb.2011.77
PMCID: PMC3261705  PMID: 22027554
dynamics; kinetics; model; ontology; simulation
3.  BioPAX – A community standard for pathway data sharing 
Demir, Emek | Cary, Michael P. | Paley, Suzanne | Fukuda, Ken | Lemer, Christian | Vastrik, Imre | Wu, Guanming | D’Eustachio, Peter | Schaefer, Carl | Luciano, Joanne | Schacherer, Frank | Martinez-Flores, Irma | Hu, Zhenjun | Jimenez-Jacinto, Veronica | Joshi-Tope, Geeta | Kandasamy, Kumaran | Lopez-Fuentes, Alejandra C. | Mi, Huaiyu | Pichler, Elgar | Rodchenkov, Igor | Splendiani, Andrea | Tkachev, Sasha | Zucker, Jeremy | Gopinath, Gopal | Rajasimha, Harsha | Ramakrishnan, Ranjani | Shah, Imran | Syed, Mustafa | Anwar, Nadia | Babur, Ozgun | Blinov, Michael | Brauner, Erik | Corwin, Dan | Donaldson, Sylva | Gibbons, Frank | Goldberg, Robert | Hornbeck, Peter | Luna, Augustin | Murray-Rust, Peter | Neumann, Eric | Reubenacker, Oliver | Samwald, Matthias | van Iersel, Martijn | Wimalaratne, Sarala | Allen, Keith | Braun, Burk | Whirl-Carrillo, Michelle | Dahlquist, Kam | Finney, Andrew | Gillespie, Marc | Glass, Elizabeth | Gong, Li | Haw, Robin | Honig, Michael | Hubaut, Olivier | Kane, David | Krupa, Shiva | Kutmon, Martina | Leonard, Julie | Marks, Debbie | Merberg, David | Petri, Victoria | Pico, Alex | Ravenscroft, Dean | Ren, Liya | Shah, Nigam | Sunshine, Margot | Tang, Rebecca | Whaley, Ryan | Letovksy, Stan | Buetow, Kenneth H. | Rzhetsky, Andrey | Schachter, Vincent | Sobral, Bruno S. | Dogrusoz, Ugur | McWeeney, Shannon | Aladjem, Mirit | Birney, Ewan | Collado-Vides, Julio | Goto, Susumu | Hucka, Michael | Le Novère, Nicolas | Maltsev, Natalia | Pandey, Akhilesh | Thomas, Paul | Wingender, Edgar | Karp, Peter D. | Sander, Chris | Bader, Gary D.
Nature biotechnology  2010;28(9):935-942.
BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.
doi:10.1038/nbt.1666
PMCID: PMC3001121  PMID: 20829833
pathway data integration; pathway database; standard exchange format; ontology; information system
4.  MathSBML: a package for manipulating SBML-based biological models 
Bioinformatics (Oxford, England)  2004;20(16):2829-2831.
Summary: MathSBML is a Mathematica package designed for manipulating Systems Biology Markup Language (SBML) models. It converts SBML models into Mathematica data structures and provides a platform for manipulating and evaluating these models. Once a model is read by MathSBML, it is fully compatible with standard Mathematica functions such as NDSolve (a differential-algebraic equations solver). MathSBML also provides an application programming interface for viewing, manipulating, running numerical simulations; exporting SBML models; and converting SBML models in to other formats, such as XPP, HTML and FORTRAN. By accessing the full breadth of Mathematica functionality, MathSBML is fully extensible to SBML models of any size or complexity.
Availability: Open Source (LGPL) at http://www.sbml.org and http://www.sf.net/projects/sbml.
doi:10.1093/bioinformatics/bth271
PMCID: PMC1409765  PMID: 15087311

Results 1-5 (5)