Multiscale Cancer Modeling

Multiscale modeling

Hybrid multiscale modeling and prediction of cancer cell behavior

BACKGROUND Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. METHODS In...

Simulating cancer growth with multiscale agent-based modeling.

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspe...

Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

In this paper, we review multiscale modeling for cancer treatment with the incorporation of drug effects from an applied system's pharmacology perspective. Both the classical pharmacology and systems biology are inherently quantitative; however, systems biology focuses more on networks and multi factorial controls over biological processes rather than on drugs and targets in isolation, whereas ...

A Multiscale, Cell-Based Framework for Modeling Cancer Development

We use a systems approach to develop a predictive model that medical researchers can use to study and treat cancerous tumors. Our multiscale, cell-based model includes intracellular regulations, cellular level dynamics and intercellular interactions, and extracellular chemical dynamics. The intracellular level protein regulations and signaling pathways are described by Boolean networks. The cel...