The Community for Technology Leaders
RSS Icon
Subscribe
Orlando, FL, USA
Feb. 3, 2011 to Feb. 5, 2011
ISBN: 978-1-61284-851-8
pp: 242-243
Jason Gallia , SUNY Binghamton Computer Science Department, USA
Anna Tan-Wilson , SUNY Binghamton Biological Sciences Department, USA
Patrick H Madden , SUNY Binghamton Computer Science Department, USA
ABSTRACT
In this paper we present a new de novo method to identify protein and peptide amino acid sequences from tandem mass spectrometry (MS/MS) data. Our approach uses an integer knapsack dynamic programming formulation, which allows for optimization to directly consider ions other than the typical b and y variety. Rather than acting as ??noise" which obscures the sequence in question, the additional ions can be used to improve identifications, and provide greater confidence in the results. We validate our approach using raw experimental data.
CITATION
Jason Gallia, Anna Tan-Wilson, Patrick H Madden, "Poster: De novo protein identification by dynamic programming", ICCABS, 2011, 2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS), 2013 IEEE 3rd International Conference on Computational Advances in Bio and medical Sciences (ICCABS) 2011, pp. 242-243, doi:10.1109/ICCABS.2011.5729896
22 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool