Department of Computer Science
Speeding up scoring module of mass spectrometry based protein identification by GPU
Database searching is a main method for protein identification in shotgun proteomics, and many research efforts are dedicated to improving its effectiveness. However, the efficiency of database searching is facing a serious challenge, due to the ever fast growth of protein and peptide databases resulted from genome translations, enzymatic digestions, and post-translational modifications (PTMs). On the other hand, as a general-purpose and high performance parallel hardware, Graphics Processing Units (GPUs) develop continuously and provide another promising platform for parallelizing database searching based protein identification. It becomes very important to study how to speed up database search engines by GPUs for protein identification. In this paper, we mainly utilize GPUs to accelerate the scoring module, which is the most time-consuming component. Specifically, we study two popular scoring method: spectral dot product based method, which is used by X!Tandem, and kernel spectral dot product, which is used by pFind. © 2012 IEEE.
GPU computing, protein identification, spectral dot product
Source Publication Title
Proceedings of the The 14th IEEE International Conference on High Performance Computing and Communications/ The 9th IEEE International Conference on Embedded Software and Systems
Liverpool, United Kingdom
Li, You, and Xiaowen Chu. "Speeding up scoring module of mass spectrometry based protein identification by GPU." Proceedings of the The 14th IEEE International Conference on High Performance Computing and Communications/ The 9th IEEE International Conference on Embedded Software and Systems (2012): 1315-1320.