Ciro de Barros Barbosa

A transformation tool for ODE based models

This paper presents a tool for prototyping ODE (Ordinary Differential Equations) based systems in the area of computational modeling. The models, tailored during the project step of the system development, are recorded in MathML, a markup language built upon XML. This design choice improves interoperability with other tools used for mathematical modeling, mainly considering that it is based on Web architecture. The resulting work is a Web portal that transforms an ODE model documented in MathML to a C++ API that offers numerical solutions for that model.

Approaching cardiac modeling challenges to computer science with CellML-based web tools

Cardiac modeling is being used in a variety of ways to support the tests of new drugs, the development of new medical devices and of non-invasive diagnostic techniques. Computer models have become valuable tools for the study and comprehension of the complex phenomena of cardiac electrophysiology. However, the complexity, the multi-scale and multi-physics nature of cardiac modeling still restrict its use to a few specialized research centers in the world. In addition, the issue of sharing and re-using such models has proven to be particularly problematic, with published models often lacking information that is required to accurately reproduce published results. In this work, with the aim of tackling the aforementioned issues, we present a web portal that provides support for cardiac electrophysiology modeling. This framework integrates different computer tools and allows one to bypass many complex steps during the development and use of cardiac models. The process of model development is supported by a Web-based editor for CellML, a mark-up language dedicated to the description of biological structures, processes and the associated models. The implementation of the cardiac cell models is automatically provided by a code generator that translates models described in CellML language to executable code that allows one to manipulate and solve the models numerically. The set up and use of the simulator is supported by a user-friendly graphical interface that offers the tasks of simulation configuration and execution, storage of results and basic visualization. All the tools are integrated in a Web Portal. As a result, the complex techniques and the know-how behind cardiac modeling are all taken care of by the web distributed applications.

Comparing high performance techniques for the automatic generation of efficient solvers of cardiac cell models

In silico experiments have been used for a better understanding of the electrical activity of cardiac myocytes, usually via models based on nonlinear systems of ordinary differential equations. Many different models for cardiac myocytes are available that vary on the level of complexity, depending on how detailed the phenomena is described. Long simulations of realistic and complex models are computationally expensive. To cope with this problem, this work compares different techniques to automatically speed up the numerical solution of cardiac models: (a) adaptive time step method, (b) Partial Evaluation (PE) and Lookup Tables (LUTs), and (c) an automatic way to find and exploit code concurrency via OpenMP directives. All the techniques were implemented as part of an automatic code generator for the numerical solution of models that are described in the CellML markup language. Experimental results demonstrated that the adaptive time step simulations were up to 32 times faster than the traditional Euler that use fixed time step. Combined with parallel computing on a multicore processor the execution time was further decreased and simulations were 41 times faster. Finally, the LUTs and PE techniques resulted in a 117-fold improvement in computation time over the Euler method and 72-fold improvement when compared to the traditional Rush–Larsen method.

A computational framework for cardiac modeling based on distributed computing and web applications

Cardiac modeling is here to stay. Computer models are being used in a variety of ways and support the tests of drugs, the development of new medical devices and non-invasive diagnostic techniques. Computer models have become valuable tools for the study and comprehension of the complex phenomena of cardiac electrophysiology. However, the complexity and the multidisciplinary nature of cardiac models still restrict its use to a few specialized research centers in the world. We propose a computational framework that provides support for cardiac electrophysiology modeling. This framework integrates different computer tools and allows one to bypass many complex steps during the development and use of cardiac models. The implementation of cardiac cell models is automatically provided by a tool that translates models described in CellML language to executable code that allows one to manipulate and solve the models numerically. The automatically generated cell models are integrated in an efficient 2-dimensional parallel cardiac simulator. The set up and use of the simulator is supported by a userfriendly graphical interface that offers the tasks of simulation configuration, parallel execution in a pool of connected computer clusters, storage of results and basic visualization. All these tools are being integrated in a Web portal that is connected to a pool of clusters. The Web portal allows one to develop and simulate cardiac models efficiently via this user-friendly integrated environment. As a result, the complex techniques and the know-how behind cardiac modeling are all taken care of by the web distributed applications.

Modeling Human Immune System Using a System Dynamics Approach

The Human Immune System (HIS) consists of a complex network of cells, tissues and organs that protects the body against invaders. Understanding how the HIS works is therefore essential to obtain new insights into its nature and to deal effectively with diseases. Computational modeling can be used for this purpose: it allows researchers to perform virtual experiments in silico, that can speed up the discovery of new drugs against diseases and reduce their cost. To create a computational model of the HIS, the behavior of its components and their relationships must be modeled using a formal language, such as those used in Mathematics. This paper presents the JynaCore, an API that uses System Dynamics instead of pure mathematical equations to model complex systems. In particular, this API is used to model and simulate the dynamics of the immune response to lipopolysaccharide (LPS) in a microscopic section of tissue.

System dynamics metamodels supporting the development of computational models of the human innate immune system

The human body is protected against pathogenic invasions by a complex system of cells, tissues and organs which form the Human Immune System (HIS). Understanding how the HIS works is therefore essential to obtain new insights into its nature and to deal effectively with diseases. Mathematical and computational modeling can be used for this purpose. Unfortunately, these complex mathematical models are very difficult to develop, understand and use by a more general and multidisciplinary team. This paper presents a System Dynamics Metamodeling tool, called JynaCore API, that supports the development of complex models using System Dynamics in a more abstract level. To demonstrate the power and usefulness of the proposed System Dynamics Metamodeling tool, in this work we present the development of a complex two-dimensional tissue model that simulates the dynamics of the immune response.

A New Web-Based Integration Tool for the Development of in Silico Experiments of Cardiac Electrophysiology

Computational modeling of cardiac electrophysiology demands multidisciplinary groups and a growing number of simulation software to validate new models with experimental data. These in silico experiments are very often composed of legacy tools developed by different researchers and based on different technologies. Therefore, they tend to be very hard to reproduce or extend. This paper presents the FISIOCOMP Environment, a web-based tool that simplifies the simulation process by allowing legacy tools to be easily integrated, documented and used in the development of new in silico experiments. In addition, a study case is presented, where a legacy command line tool for simulating cardiac electrophysiology models is integrated in a new userfriendly web application that allows one to perform sensitivity analysis of the model’s parameters. This new web application is then used to support the study of some pathological changes observed by in vitro experiments performed with ventricular cardiac myocytes extracted from infected mice that are in the acute phase of Chagas’ Disease.