Crowd sourcing difficult problems in protein science^*

Abstract

Dedicated computing resources are expensive to develop, maintain, and administrate. Frequently, research groups require bursts of computing power, during which progress is still limited by available computing resources. One way to alleviate this bottleneck would be to use additional computing resources. Today, many computing devices remain idle most of the time. Passive volunteer computing exploits this unemployed reserve of computing power by allowing device-owners to donate computing time on their own devices. Another complementary way to alleviate bottlenecks in computing resources is to use more efficient algorithms. Engaging volunteer computing employs human intuition to help solve challenging problems for which efficient algorithms are difficult to develop or unavailable. Designing engaging volunteer computing projects is challenging but can result in high-quality solutions. Here, we highlight four examples.

PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics

“…The tools, however, are limited in their availability, search accuracy as well as run-time performance ( 8–11 ). Furthermore, limited features for non-commercial users ( https://assets.thermofisher.com/TFS-Assets/CMD/manuals/Man-XCALI-97801-ProSightPC-User-ManXCALI97801-EN.pdf ) impede wider employment of these tools while the general lack of open source code ( 12 , 13 ) hinders their community-based software development ( 14 ).…”