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Software for Peptide Identification and Quantification from Large Mass Spectrometry Data using Data Independent Acquisition

2017 Bioinformatics and Computational Biology Competition
Genome Centre(s):
Ontario Genomics
Project Leader(s):
Bin Ma (University of Waterloo), Michael Moran (Hospital for Sick Children)
Project Description: 

Precision medicine gives patients the opportunity to tailor medical and treatment decisions at the individual level to maximize outcomes and minimize adverse effects. It can be used to treat a wide variety of diseases, including cancer. Decisions are often based on the presence and quantity of biomarkers such as proteins in the blood or tissue samples.

Advances in mass spectrometry instruments have made it feasible to discover and measure protein biomarkers, but researchers lack the necessary bioinformatics software to analyze the data. Drs. Bin Ma of the University of Waterloo and Michael Moran of the Hospital for Sick Children are developing this software to enable more sensitive and accurate protein identification and quantification from the mass spectrometry data generated using a method called data independent acquisition (DIA). They expect that their software will significantly increase the total number of proteins identified and quantified in comparison to existing DIA analytical software. It will be especially effective with post-translational modifications (PTMs), which are critical biomarkers in a proteins’ function and degradation.

The free availability of the software to academic labs coupled with its superior performance can help health researchers discover and trace disease biomarkers. Within the next decade, the software could become an indispensable tool for many proteomics labs performing DIA analysis throughout the world. The new software may also help commercial partners create value-added new products, services and jobs.

Ultimately, this will lead to improvements in human health and reduction in healthcare costs by enabling early disease detection and diagnosis and by facilitating the selection of optimal treatment for individual patients.