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T Nomura 1,2 , Y. Asai 2 , K Hagihara 2,3 and Y Kurachi 2,4

An open platform for physiome and systems biology: insilicoML and IDE as a CellML compatible model sharing environment. T Nomura 1,2 , Y. Asai 2 , K Hagihara 2,3 and Y Kurachi 2,4 Division of Bioengineering, Graduate School of Engineering Science, Osaka University

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T Nomura 1,2 , Y. Asai 2 , K Hagihara 2,3 and Y Kurachi 2,4

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  1. An open platform for physiome and systems biology: insilicoML and IDE as a CellML compatible model sharing environment • T Nomura1,2, Y. Asai2, K Hagihara2,3 and Y Kurachi2,4 • Division of Bioengineering, Graduate School of Engineering Science, Osaka University • The Center for Advanced Medical Engineering and Informatics, Osaka University • Department of Computer Science, Graduate School of Information Science and Technology • Department of Pathophysiology and Therapeutics, Graduate School of Medicine, Osaka University SIAM Model Sharing Panel, 4th Aug, 2008, Montreal

  2. Integrated Biosciences and Bioengineering are moving the world towards a new generation of life sciences Molecular Level Cellular Level Organ Level Individual level Molecular Models Cell models Organ models Individual models The sequencing of the human genome was an epoch marking event, liberating exhaustive experimental data in the reductionist life science. Advances in techniques for non-invasive measurement of human body functions, information technology and the applied mathematics continue their remarkable development. Physiome and Systems Biology Multiple scale modeling and simulations of human functions (Systems biology) Databases covering multiple scale human structure and functions (Physiome) in silico human Establishment of “in silico human” will be able to provide solutions for clinical problems based upon understanding of the dynamic mechanisms of human physiology and pathology. Trials in silico for drug discovery, medical/welfare apparatus improves the development of products with higher efficiency, reliability and safety while reducing cost.

  3. Physiome.jp as a Worldwide Open Platform for Physiome and Systems Biology

  4. in silico Human Project@Physiome.jp MPI source codes Multi-Scale Mathematical Models XPPaut ode-files Ontology for semantically but quantitatively linking models insilico Model DB (ISML and ISDB) heart cell, transporters, human motion, lung, mechanical tissues compatible analysis Bunki@ERATO Arrythmo Predictor Matlab scripts compatible documentation LaTeX MathType Model-Specific Parameter Sets Multi-Scale Dynamic Data ISIDE workspace Model Construction Local and HP-Computations Musculo-Skeletal system Face/Mouth characteristics Pharmacophore Cardiac Cell excitation Face/mouth motion Body motion … Tissue stiffness Drug Metabolism and interaction … … Elastic response of tissue Multi-Scale Anatomical Data References Morphology Model DB Publications PubMed, Scopus Constructing Ontology Morphology Image DB

  5. Physiome.jp as a Model Sharing Platform - Enhancing Knowledge Integration -

  6. Available at http://www.physiome.jp Model Construction and Simulation ISDB Model Reuse ISIDE Model Reuse Save as CellML CellML 1.0 Model Repository Save as ISML PCEnv0.4 Model Registration Model Reuse ISML Morphology Model DB ISIDE

  7. Some Features of (ISML, ISDB, ISIDE) Capable of models with morphology Linking between models in-out ports with different physical units is warned for reduction of incorrect model reuse Capable of automatically generating MPI parallel codes

  8. A Questionnaire Survey on the Model Sharing in the Model-Related Life Science Fields in Japan Physiome and Systems Biology Initiative Japan F. Kajiya (Kawasaki) H. Kitano (Systems Biology Institute) Y. Kurachi (Osaka) M. Suematsu (Keio) T. Nomura (Osaka) R. Himeno (RIKEN) Y. Matsumoto (Tokyo)

  9. Research Fieldsof Respondents • Biomedical Engineering • Physiology, Medical Sciences • Biomechanics • Bioinformatics, Systems Biology • Neuroscience, Neuroinformatics • Mathematical Biology and Others

  10. Select one as your attitude to Model Sharing Systems • No interest and I will not use the system • I will use the system but not contribute • I will use the system and contribute • I will actively use the system and contribute

  11. Scopus h-index dependency of the answers for Q1 • No interest and will never use • I will use the system but not contribute • I will use the system and contribute • I will actively use the system and contribute

  12. Select one or more formats suitable for Model Sharing • Model description formats for existing simulation software • Program source codes • XML-like model description formats with their interpreters • Others

  13. Select one of 4 organizations suitable for maintaining Model Sharing Systems • Academic society including NPO • Educational Institute/University • National Institute • Others

  14. Select an appropriate timing of your model publicity for sharing • I will not share my model with others • One or more year(s) after my paper publication • Quickly after my paper publication • Open for the referee and at the same time with my paper publication

  15. Select one as your opinion for setting a Model Sharing policy by journal(s) in your field • I will not agree and oppose such a policy • I will not actively agree but accept for several journals • Good for some journals to set such a policy for promotion of science • Actively agree with such a policy for promotion of science

  16. Select one or more Model Sharing System(s) that you have been used or are planning to use 1. BioModels.net (EMBL-EBI) Database http://www.ebi.ac.uk/biomodels/ 2. e-cell SBML model repository http://www.e-cell.org/ecell-models/repository/SBML 3. CellMLmodel repository http://www.cellml.org/models 4. NSR Physiome Models http://physiome.org/Models/ 5. NEURON model database http://senselab.med.yale.edu/modeldb/ 6. insilicoDB model databasehttp://www.physiome.jp 7. INCF Japan Node Visiome http://platform.visiome.neuroinf.jp/modules/xoonips/ 8. simBio http://www.sim-bio.org/model/ 9. The Center for Cardiovascular Bioinformatics and Modeling http://www.ccbm.jhu.edu/software/models.php 10. National Resource for Cell Analysis and Modelinghttp://www.nrcam.uchc.edu/applications/published _models.html 11. SimBios https://simtk.org/xml/index.xml 12. Others

  17. Comments Made by the Respondents Taking every detail of a published model non-public is like publishing a scientific paper in molecular biology without taking gene sequences public. Thus the model sharing by means of numerically verifiable manner is not surprising, and it will lead to a new spiral of intellectual scientific activity such as impacted by Science 2.0. If the model sharing is going to be made by means of Open-Source like policy, it is preferable that the systems are run not by policies of scientific journals and societies but by certain organizations such as OBF (Open Bio Foundation) based on voluntary movement of the researchers. Otherwise, without sufficient incentive mechanisms, this field will loose top-class personnel for developing software. • Necessity of: • - international agreements to establish the system-managing organization • - long range sufficient financial and human-resource supports to run the system • (automatic) model-curation mechanisms • development of quantitative ontology providing for explosion of the number of models • peer review for a submitted model in addition to journal review • education system compensating easy-use of shared models • linking to the original paper, references, and related educational models to simulate • incentive mechanisms for contribution to the model sharing • incentive mechanisms for maintaining the systems

  18. Collaborators Yoshiyuki Asai, PhD ISML-DB-IDEChief Developer Masakazu Yagi, PhD Face and Mouth Motion Kenji Yamada, PhD Tissue Stiffness Rachid Ait-Haddou, PhD Morphological Modeling Ca2+ dynamics Yoshiyuki Kido, PhD Database and Ontology Yoshiyuki Kagiyama, PhD Image Processing Daisuke Yamasaki, PhD Pharmacophore Kunichika Tumoto, PhD Cardiac Cell Dyanmics Hideki Oka, PhD (FEM and HPC) Takahito Urai (Programming) Tatsuhide Okamoto (Model Creator) Eric Hien (HPC, Grid, Math-Editor) Masao Nakanishi (Large Scale Modeling) Yasuyuki Suzuki (Musculo-Skeletal System) Yosuke Yumikura (Ca2+ Dyanamics) Toshihiro Kawazu (Programming, Ca2+ Dyanamics) Masanori Ato (Pharmaco-Dynamics) Kazuyoshi Kawa (Constraint Dynamics)

  19. Multi-Level Appendix

  20. Integrative Knowledge Database as a Tool of the Physiome Project Data Registration (upload) Data Search (download) Experimental-Data Databases Exploring human body and functions “in silico” across multiple scales of time and size and through diverse hierarchies of organization Integrative Knowledge Database Collaboration for Model Construction Model Registration (upload) Model Search (download) Mathematical Model Databases Personal and Large Scale Dynamic Simulations

  21. Why Databases? Handling Complexity and Hierarchy of Physiological Functions for Quantitative Integration Sub-Cellular Level Cell Level Kawazu et al Molecular Level Kamiya et al

  22. Morphological Modeling of Dyadic Space using ISIDE Geometry of channels Experimental data (Calcium ion current) Imredy, J.P. & Yue, D.T. 1992. Neuron Simulation Results (Calcium ion current) 10ms 0.002pA

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