Organizers: David Phillip Nickerson, Peter Hunter
The Physiome journal was recently established by the IUPS to help encourage scientists to make their computational models available such that they are Findable, Accessible, Interoperable, and Reusable (FAIR). Physiome publishes models and data that are associated with a peer-reviewed and accepted primary article, with the Physiome editors and curators helping the authors ensure their work is as FAIR as possible. This includes making sure that appropriate model and data encoding standards are used, sufficient annotation is included to ensure other scientists are able to comprehend and reuse the work, and that simulation predictions are reproducible.
This tutorial will begin with a series of short presentations introducing Physiome, reviewing example submissions spanning spatial scales and types of physics, and key software tools, model encoding standards, and repositories. The Physiome submission, curation, and publication workflow will also be discussed. A bond-graph-based method for formulating mathematical models in an energy-conserving manner to improve reuse will also be presented. Following the presentations, tutors will be available to help attendees work through example Physiome submissions using either prepared demonstration materials or their own models and/or data. Attendees are also encouraged to raise issues specifically related to their work with the tutors.
In addition to Physiome (https://journal.physiomeproject.org), the following tools and technologies will be covered in this tutorial: CellML (https://cellml.org); FieldML (http://fieldml.org/); OpenCOR (http://opencor.ws); OpenCMISS (http://opencmiss.org); COMBINE (http://co.mbine.org); Physiome Model Repository (https://models.physiomeproject.org); MAP client (http://map-client.readthedocs.org).
List of Speakers
Peter J Hunter, Auckland Bioengineering Institute
Peter is the founding Director of the Auckland Bioengineering Institute as well as holding honorary and visiting Professorships at a number of universities around the world and currently 2nd Vice President of IUPS. Peter is one of the leaders in worldwide efforts to develop a virtual physiological human.
David P Nickerson, Auckland Bioengineering Institute
David received his PhD in Bioengineering at Auckland University working on modelling cardiac electromechanics. He has been involved in CellML since its inception in the late ‘90s and is currently an editor of the CellML and SED-ML specifications and a COMBINE coordinator. David is currently an Aotearoa Foundation Fellow at the ABI.
Poul Nielsen, Auckland Bioengineering Institute
Poul Nielsen is a Professor affiliated with the Auckland Bioengineering Institute and Department of Engineering Science at the University of Auckland. His research interests include soft tissue mechanics, instrumentation, and the representation of biological models. He has been closely affiliated with the Physiome and CellML projects since their inception.
Hugh Sorby, Auckland Bioengineering Institute
Hugh Sorby is a Senior Software Specialist in the Auckland Bioengineering Institute at the University of Auckland. Hugh has over ten years’ experience in developing scientific software across a wide variety of application areas. He is the project manager and lead developer of the Musculoskeletal Atlas Project (MAP) client and contributes to the development of the software supporting the Physiome Model Repository and CellML.
Alan Garny, Auckland Bioengineering Institute
Alan Garny is a senior software consultant at the Auckland Bioengineering Institute, working from the French Riviera. He holds a DPhil from the University of Oxford, where he worked in the field of cardiac electrophysiological modelling. He is currently a CellML editor, as well as the project manager and lead developer of OpenCOR.
Soroush Safaei, Auckland Bioengineering Institute
Soroush received his PhD in Bioengineeing at the University of Auckland working in the Physiome project group. His PhD research focused on developing a comprehensive framework for modelling the human vascular system using computational methods. He is continuing his academic career as a post-doctoral research fellow at the Auckland Bioengineering Institute. His research interests include modelling cardiovascular system, diabetes, and biochemical systems using CellML, OpenCMISS and bond graphs.
Thiranja Prasad Babarenda Gamage, Auckland Bioengineering Institute
Prasad received his PhD in Bioengineering at Auckland University working on constitutive parameter identifiability and the design of experiments for applications in breast cancer diagnosis and treatment. He is currently a research fellow at the ABI. His research involves developing patient specific biomechanical models across several organ systems (breast, skin, lung, heart) to help improve the diagnosis and treatment of diseases. His modelling makes use of the OpenCMISS computational modelling software and has been a core developer on the project for the past 9 years.
Vijay Rajagopal, University of Melbourne
Vijay Rajagopal is a Senior Lecturer at the Department of Biomedical Engineering at the University of Melbourne. He was awarded a PhD in patient-specific biomechanical modelling with applications in breast cancer. His current research interests encompass the development of innovative experimental and computational modelling approaches to study biological remodelling of cells and tissues. His team leads the Cardiac Cell Physiome Project, an effort to develop quantitative models of the sub-cellular processes that govern cardiac cell physiology. His team actively contributes to the development of Physiome tools such as OpenCMISS and are also leading the development of a Physiome Portal for sharing models of cells.
Kenneth Tran, Auckland Bioengineering Institute
Kenneth Tran is a Research Fellow at the Auckland Bioengineering Institute focused on using an interdisciplinary approach of bioinstrumentation, experimentation and computational modelling to understand the disease mechanisms associated with heart failure. His research interests include using bond graphs and CellML to represent models of cardiac cellular function.