A method for visualizing CellML models

被引:9
|
作者
Wimalaratne, S. M. [1 ]
Halstead, M. D. B. [1 ]
Lloyd, C. M. [1 ]
Cooling, M. T. [1 ]
Crampin, E. J. [1 ,2 ]
Nielsen, P. F. [1 ,2 ]
机构
[1] Univ Auckland, Auckland Bioengn Inst, Auckland 1, New Zealand
[2] Univ Auckland, Dept Engn Sci, Auckland, New Zealand
关键词
COLLABORATIVE CONSTRUCTION; FUTURE; TOOLS;
D O I
10.1093/bioinformatics/btp495
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: The Physiome Project was established in 1997 to develop tools to facilitate international collaboration in the physiological sciences and the sharing of biological models and experimental data. The CellML language was developed to represent and exchange mathematical models of biological processes. CellML models can be very complicated, making it difficult to interpret the underlying physical and biological concepts and relationships captured/described in the mathematical model. Results: To address this issue a set of ontologies was developed to explicitly annotate the biophysical concepts represented in the CellML models. This article presents a framework that combines a visual language, together with CellML ontologies, to support the visualization of the underlying physical and biological concepts described by the mathematical model and also their relationships with the CellML model. Automated CellML model visualization assists in the interpretation of model concepts and facilitates model communication and exchange between different communities.
引用
收藏
页码:3012 / 3019
页数:8
相关论文
共 50 条
  • [31] Measuring and Visualizing Learning with Markov Models
    Abu Deeb, Fatima
    Kime, Kristian
    Torrey, Rebecca
    Hickey, Timothy
    2016 IEEE FRONTIERS IN EDUCATION CONFERENCE (FIE), 2016,
  • [32] Parameter identifiability of cardiac ionic models using a novel CellML least squares optimization tool
    Hui, Ben B. C. B.
    Dokos, Socrates
    Lovell, Nigel H.
    2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16, 2007, : 5307 - 5310
  • [33] Generative models for visualizing idiosyncratic impressions
    Todorov, Alexander
    Uddenberg, Stefan
    Albohn, Daniel
    BRITISH JOURNAL OF PSYCHOLOGY, 2023, 114 (02) : 511 - 514
  • [34] Visualizing Statistical Models: Removing the Blindfold
    Wickham, Hadley
    Cook, Dianne
    Hofmann, Heike
    STATISTICAL ANALYSIS AND DATA MINING, 2015, 8 (04) : 203 - 225
  • [35] Models, objects, and ghosts: visualizing history
    Staley, David J.
    Asmussen, Benjamin
    MANAGEMENT & ORGANIZATIONAL HISTORY, 2023, 18 (01) : 97 - 110
  • [36] Visualizing parameters from loglinear models
    Pedro Valero-Mora
    María F. Rodrigo
    Forrest W. Young
    Computational Statistics, 2004, 19 : 113 - 135
  • [37] MML Toolkit and Work Flow Overview: Creating Temporo-Spatial Heart Models From CellML
    Chang, David C.
    Dokos, Socrates
    Lovell, Nigel H.
    2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2010, : 1481 - 1484
  • [38] Comments on "Visualizing Statistical Models": Visualizing Modern Statistical Methods for Big Data
    Allen, Genevera I.
    Campbell, Frederick
    Hu, Yue
    STATISTICAL ANALYSIS AND DATA MINING, 2015, 8 (04) : 226 - 228
  • [39] SBML and CellML translation in Antimony and JS']JSim
    Smith, Lucian P.
    Butterworth, Erik
    Bassingthwaighte, James B.
    Sauro, Herbert M.
    BIOINFORMATICS, 2014, 30 (07) : 903 - 907
  • [40] Experience report: A Haskell interpreter for CellML
    Cooper, Jonathan
    McKeever, Steve
    ACM SIGPLAN Notices, 2007, 42 (09): : 247 - 250