- Computer Models
- About the Computational Systems Biology Laboratory
For further information about the Computational Systems Biology Laboratory, contact Dr. Ranjan Dash.
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Led by Dr. Ranjan Dash, research in the Computational Systems Biology Laboratory uses signal- and system-engineering methodologies, in conjunction with experimental measurements, to develop multi-scale mechanistic computational models. These models will further the quantitative and integrated understanding of the biophysical and biochemical operations of a variety of biological/physiological systems and guide engineering-based manipulations of the same. CSBL research involves applications of efficient numerical methods and algorithms for model parameter optimization to experimental data—which can be large-scale, requiring parameter sensitivity analysis—a major task for calibrating the models and gaining mechanistic insights into the function of biological/physiological systems.
The behavior of biological systems is usually non-intuitive and nonlinear, making it difficult to understand how such systems function in health, are disrupted in disease, and are impacted by potential treatments. Understanding how all components of a biological system work together and how a change in one component impacts all other components is often referred to as Systems Biology.
To a biomedical engineer, Systems Biology is concerned with the study of biological functions and processes via signal- and system-oriented engineering approaches. Computational Systems Biology uses computers to develop and apply predictive computational models, efficient numerical methods, data structures, and simulation and visualization tools for biological processes. Examples include using computer simulations of cellular systems and subsystems such as metabolism, signal transduction pathways, and gene regulatory networks to analyze the complex interactions of involved processes.