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Recent advancement in the biological sciences field led to an increase in the development of large biological software research projects. These projects are complex and interconnected and have proven to be hard to manage. In many cases, these projects are not completed within their deadlines and fail to provide the users with a reliable piece of software that can be managed and maintained in the future. This observation was also confirmed by scientists working in other research and scientific fields. It is well known that the non-deterministic nature of science requires it to be always evolving and changing. To meet such requirements using conventional software engineering practices will be a very hard goal to achieve. For this reason, I suggest the use of agile approaches such as Scrum, Kanban, and extreme programming, as an attractive choice to many developers working in many academic and scientific fields especially in areas such as computational biology. In this paper, I will discuss some biological software systems that used agile approaches in developing or enhancing their projects and I will look into the benefits gained from adopting those approaches and how it can benefit the outcome of many scientific projects.

Planning Computational Biology Projects Using Agile Approach