• DocumentCode
    653992
  • Title

    Biocharts: Unifying Biological Hypotheses with Models and Experiments

  • Author

    Kugler, Hillel

  • fYear
    2013
  • fDate
    22-25 Oct. 2013
  • Firstpage
    317
  • Lastpage
    325
  • Abstract
    Understanding how biological systems develop and function remains one of the main open scientific challenges of our times. An improved quantitative understanding of biological systems, assisted by computational models is also important for future bioengineering and biomedical applications. We present a computational approach aimed towards unifying hypotheses with models and experiments, allowing to formally represent what a biological system does (specification) how it does it (mechanism) and systematically compare to data characterizing system behavior(experiments). We describe our Biocharts framework geared towards supporting this approach and illustrate its application in several biological domains including bacterial colony growth, developmental biology, and stem cell population dynamics.
  • Keywords
    biology computing; optimisation; bacterial colony growth; biocharts framework; bioengineering applications; biological hypotheses; biomedical applications; computational models; data characterizing system behavior; developmental biology; stem cell population dynamics; Biological system modeling; Computational modeling; Microorganisms; Object oriented modeling; Semantics; Computational Systems Biology; Developmental Biology; Stem Cells; Temporal Logic; Visual Formalisms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    eScience (eScience), 2013 IEEE 9th International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/eScience.2013.41
  • Filename
    6683923