Studying the human genome is the world’s largest project, but the work can be slow — even with computers.

Renowned for its innovation in medical research and genomics, Harvard Medical School wanted to speed the process of standard DNA sequencing, which is essential for making precise, high-throughput readouts of the immune system. A full-time employee had worked for a year to optimize an algorithm that calculates the distance between DNA strings, but they wanted to see if more data scientists working on the problem could deliver even better results.

With an Analytics Starter Pack from Topcoder, Harvard received on-demand access to more than 120 data scientists who worked to optimize the algorithm for two weeks. Competitors submitted more than 650 possible solutions using 89 unique approaches to the problem.

The final result delivered by Topcoder was extraordinary, increasing the speed of their algorithm from 260.4 minutes to just 16 seconds — 976 times faster. This extreme value outcome not only enabled Harvard to accelerate their study of genetics as a unified way to extract organizing principles, but it also shifted the way they approach genetics research.

Topcoder surpassed expectations: a two-week competition led to code that was just as good but almost three orders of magnitude faster for a few thousand dollars. Hard to imagine beating that.

Data Scientists
122
Submissions
654
Unique Approaches
89
Duration
2 Weeks