Biocoder: A programming language for standardizing and automating biology protocols

We have developed BioCoder, a C++ library that enables biologists to express the exact steps needed to execute a protocol. In addition to being suitable for automation, BioCoder converts the code into a readable, English-language description for use by biologists. We have implemented over 65 protocols in BioCoder; the most complex of these was successfully executed by a biologist in the laboratory using BioCoder as the only reference. We argue that BioCoder exposes and resolves ambiguities in existing protocols, and could provide the software foundations for future automation platforms. BioCoder is freely available for download at http://research.microsoft.com/en-us/um/india/projects/biocoder/ webcite.BioCoder represents the first practical programming system for standardizing and automating biology protocols. Our vision is to change the way that experimental methods are communicated: rather than publishing a written account of the protocols used, researchers will simply publish the code. Our experience suggests that this practice is tractable and offers many benefits. We invite other researchers to leverage BioCoder to improve the precision and completeness of their protocols, and also to adapt and extend BioCoder to new domains.For decades, biologists have relied on written descriptions of protocols to guide their experiments in the laboratory. However, due to recent technology trends, the practice of describing protocols with free-flowing English-language text is quickly becoming inadequate and obsolete. First, we are witnessing immense advances in laboratory automation systems. The increasing density of microfluidic devices has been compared to Moore's Law [1,2], with recent products supporting up to 9,216 parallel reactions [3]. In order to leverage such technologies for biological experimentation, it will be necessary to express the protocols in a format that is not only comprehensible by humans, but also by machines. Second, the complexity of biology protocol