Digital Commons Network^™

High-Performance Reductive Strategies For Big Data From Lc-Ms/Ms Proteomics, Muaaz Gul Awan

Dissertations

Mass Spectrometry (MS)-based proteomics utilizes high performance liquid chromatography in tandem with high-throughput mass spectrometers. These experiments can produce MS data sets with astonishing speed and volume that can easily reach peta-scale level, creating storage and computational problems for large-scale systems biology studies. Each spectrum output by a mass spectrometer may consist of thousands of peaks, which must all be processed to deduce the corresponding peptide. However, only a small percentage of peaks in a spectrum are useful for further processing, as most of the peaks are either noise or are not useful. Our experiments have shown that 90 to …

A Holistic Computational Approach To Boosting The Performance Of Protein Search Engines, Majdi Ahmad Mosa Maabreh

Dissertations

Despite availability of several proteins search engines, due to the increasing amounts of MS/MS data and database sizes, more efficient data analysis and reduction methods are important. Improving accuracy and performance of protein identification is a main goal in the community of proteomic research. In this research, a holistic solution for improvement in search performance is developed.

Most current search engines apply the SEQUEST style of searching protein databases to define MS/MS spectra. SEQUEST involves three main phases: (i) Indexing the protein databases, (ii) Matching and Ranking the MS/MS spectra and (iii) Filtering the matches and reporting the final proteins. …