A Django-based project--ÜberFly--was designed to address the challenges in genomic data analysis. The serendipitous incorporation of IPython Notebook enabled biologists, data scientists and developers to work concurrently, generating biological analyses while providing feedback on the development of the system. The constantly evolving system seeks to accelerate the progress of biology research.
Initially a database project in National University of Singapore, to address issues in handling genomic data in biology laboratories, the ÜberFly system–written in Django–provides a bridge between biologists, data scientists and developers to work in a systematic workflow for research. Parallel to the MVT architecture of the Django web framework, the abstraction of the system at three levels–database backend, IPython Notebook and web browser–enable users of different levels of programming expertise to utilize the system to their advantage. The continuous communication and feedback between biologists, data scientists and developers provide a method for refinement and development of analytic tools for biological research. In a laboratory setting, an implementation of this system provides an avenue to let beginners in Python understand how the Python language, community and third party packages can help improve the quality of biological research. The IPython Notebook incorporation provides an added emphasis on reproducible research as well as the learnability of Python using existing notebooks used for biological analyses. An implement of the system will change how research is carried out in biological laboratories, in both streamlining research processes, as well as fostering a positive learning environment for scientists to pick up Python as a programming language.