Computational Systems Biology

Computational Systems biology is a relatively new arm of systems biology. Computational systems biology aims to develop and use efficient algorithms, data structures and communication tools to orchestrate the integration of large quantities of biological data with the goal of modeling, and others. This field essentially looks at a cell as a system and hence it is understood that biological systems are results of interplay of the cause-and-effect among simpler, integrated parts. Computational systems biology allows you to compute large amount of biological data and derive knowledge out of it. Till now the approach to biology had been reductionist one i.e. look at the genes or proteins in isolation, but with the accumulation of large number of biological data and development of computational data mining techniques, it is imperative to come up with new approaches to look at biology through the prism of Computation and relate different types of biological data. In other words, the time has come to look at the big picture. Computational systems biology strives to do just that. It is a very new field and much needs to be done.

Enough of text book definitions ! To me, computational systems biology means computing life at systems level. Since, in this field we are studying at systems level, it allows for better implementation of the engineering principles to biology or at least that is my conclusion. This field has profound impacts on neighbouring fields such as synthetic biology and bioengineering.