DNA sends the coded message to RNA for the onward transmission of message to proteins. For a long time people thought that once the ‘DNA tap' is open, the message will flow out uniformly. Not any longer. Some of the recent experiments have demonstrated that the transmission of DNA's message to RNAs and proteins looks more like perfume spray, with the intensity of gene and protein expression being highly fluctuating. Technically we know this as genetic noise. In parallel, molecular biology experiments have shown that cellular edits in the form of addition, deletion or replacement of genes frequently result in unexpected cellular behaviors.

It is interesting that the information travels at least six magnitude in size from H-atom to the whole cell level. Understanding such a system that shows spatial, temporal and contextual complexity optimized for millions of years is clearly non-trivial. Is there an alternate way to understand how biological systems function?

In the summer of 2004, people at MIT took an audacious step towards exploring the possibility of engineering organisms by organizing the first conference of Synthetic Biology. The questions that formed the basis of this new approach were simple. Can we compose organisms from scratch? Can we perform precise network edits and biologically engineer organisms towards predetermined behaviors? If yes, what are the key requirements, the best case scenarios and boundary conditions of compiling organisms?

Synthetic Biology is defined as a controllable construction of biological systems from scratch. The intended meaning of "synthetic" is not chemical, as the term might tend to indicate. Several alternative terms like constructive biology, biological technology, biodesign, biosystems engineering have appeared to emphasize construction of biological systems part-by-part.

Some of the key features of the synthetic biology approach, include abstraction of biological systems into parts, devices and circuits; building an inventory of well characterized parts; making a bio-truth table; developing data extraction and data exchange standards; identifying the rules of composition; inventing technologies for rapid synthesis and rapid assembly of parts; and developing a BioCAD platform.