• DocumentCode
    57634
  • Title

    ENISI SDE: A New Web-Based Tool for Modeling Stochastic Processes

  • Author

    Yongguo Mei ; Carbo, Adria ; Hoops, Stefan ; Hontecillas, Raquel ; Bassaganya-Riera, Josep

  • Author_Institution
    Virginia Bioinf. Inst., Virginia Tech, Blacksburg, VA, USA
  • Volume
    12
  • Issue
    2
  • fYear
    2015
  • fDate
    March-April 2015
  • Firstpage
    289
  • Lastpage
    297
  • Abstract
    Modeling and simulations approaches have been widely used in computational biology, mathematics, bioinformatics and engineering to represent complex existing knowledge and to effectively generate novel hypotheses. While deterministic modeling strategies are widely used in computational biology, stochastic modeling techniques are not as popular due to a lack of user-friendly tools. This paper presents ENISI SDE, a novel web-based modeling tool with stochastic differential equations. ENISI SDE provides user-friendly web user interfaces to facilitate adoption by immunologists and computational biologists. This work provides three major contributions: (1) discussion of SDE as a generic approach for stochastic modeling in computational biology; (2) development of ENISI SDE, a web-based user-friendly SDE modeling tool that highly resembles regular ODE-based modeling; (3) applying ENISI SDE modeling tool through a use case for studying stochastic sources of cell heterogeneity in the context of CD4+ T cell differentiation. The CD4+ T cell differential ODE model has been published [8] and can be downloaded from biomodels.net. The case study reproduces a biological phenomenon that is not captured by the previously published ODE model and shows the effectiveness of SDE as a stochastic modeling approach in biology in general and immunology in particular and the power of ENISI SDE.
  • Keywords
    bioinformatics; cellular biophysics; differential equations; human computer interaction; stochastic processes; user interfaces; CD4+ T cell differentiation; ENISI SDE; bioinformatics; cell heterogeneity; complex existing knowledge engineering; computational biologists; computational biology; immunologists; mathematics; regular ODE-based modeling; stochastic differential equations; stochastic modeling techniques; user-friendly tools; user-friendly web user interfaces; web-based tool; Biological system modeling; Computational modeling; Mathematical model; Noise; Numerical models; Object oriented modeling; Stochastic processes; Computational biology; differential equations; modeling; modeling tools; simulations; stochastic differential equations; stochastic modeling; web interface;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2014.2351823
  • Filename
    6892967