Advances in Computational Methods in Systems Biology

Advances in Computational Systems Biology

Computational Systems Biology, a rapidly evolving field, is at the interface of computer science, mathematics, physics and biology. It endeavours to study, analyze and understand complex biological systems by taking a coordinated integrated systems view using computational methodologies. From the middle of the twentieth century till present, we have been witnessing breakthrough discoveries in b...

Systemic Approaches in Bioinformatics and Computational Systems Biology : Recent Advances

Computational methods in synthetic biology.

We discuss how a theoretical synthetic biology research programme may liberate empiricism in biological sciences beyond the unaided human brain. Because synthetic biological systems are relatively small and largely independent of evolutionary contexts, they can be represented with mathematical models strongly founded on first principles of molecular biology and laws of statistical thermodynamic...

Computational Systems Biology in Cancer: Modeling Methods and Applications

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to...

Bayesian methods in bioinformatics and computational systems biology

Bayesian methods are valuable, inter alia, whenever there is a need to extract information from data that are uncertain or subject to any kind of error or noise (including measurement error and experimental error, as well as noise or random variation intrinsic to the process of interest). Bayesian methods offer a number of advantages over more conventional statistical techniques that make them ...