With Big Data Comes Big Responsibility

As the cost of genetic sequencing has fallen, the rate of data generation is outpacing our resources to analyze it. While a future in which we use low-level biological data about ourselves to inform our medical choices is inevitable, getting there will not happen by default. Current attitudes towards software in the life science and medical space are rooted in academia, but need to shift if we are to make true precision medicine a reality. The job will fall on us software engineers to develop high-quality open-source tools, build communities to support them, and transition organizations from siloed datacenters to cloud environments. We will compare bioinformatics to cryptography, a field that has successfully leveraged open-source technology to make the Internet a safer place. We will also explore specific examples of APIs and libraries that are beginning to enable this shift and are already providing benefits to their users.