PROJECT TITLE :

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

ABSTRACT:

Modeling and simulations approaches are widely utilized in computational biology, arithmetic, bioinformatics and engineering to represent complex existing data and to effectively generate novel hypotheses. Whereas deterministic modeling strategies are widely employed in computational biology, stochastic modeling techniques aren't as common thanks to a scarcity of user-friendly tools. This paper presents ENISI SDE, a completely unique net-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 3 major contributions: (one) discussion of SDE as a generic approach for stochastic modeling in computational biology; (a pair of) development of ENISI SDE, a internet-primarily based user-friendly SDE modeling tool that highly resembles regular ODE-primarily based modeling; (3) applying ENISI SDE modeling tool through a use case for finding out stochastic sources of cell heterogeneity in the context of CD4+ T cell differentiation. The CD4+ T cell differential ODE model has been printed [8] and can be downloaded from biomodels.web. The case study reproduces a biological phenomenon that's not captured by the previously published ODE model and shows the effectiveness of SDE as a stochastic modeling approach in biology generally and immunology in explicit and the facility of ENISI SDE.


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