Rob Mortiz

Rob Mortiz

Talk Title: Quantitative Proteomics in wellness and disease settings


Dr. Robert Moritz is Faculty member and Head of Proteomics Research at the Institute for Systems Biology (ISB) in Seattle Washington.

He began his career at the Ludwig Institute for Cancer Research, Melbourne, Australia in 1983 and moved to the ISB as faculty member in 2008.

His research interests in proteomics include the discovery of normal and disease markers using targeted quantitative mass spectrometry. Specifically, his group develops proteomics tools and applies these to biomarker studies for infectious diseases, lung abnormalities and other human diseases such as kidney disease, diabetes and cancer.

The Moritz group is a primary developer of proteomics software tools and pipelines for statistical validation of proteome identifications such as the world renowned Trans-Proteomic Pipeline, protein crosslinking interpretation with the program suite Kojak and online resources for quantitative proteomics under the PeptideAtlas resource. His group has developed the complete Human Peptide- and SRM-Atlas, the SWATHAtlas and software routines for SWATH data analysis to provide quantitative resources and community driven repositories of mass spectrometric assays to all proteins.

Dr. Moritz is currently the Vice-President of the Human Proteome Organization (HUPO) and plays a large role in growing the society. He has authored more than 230 papers and holds several patents in technology development and discovery protein science of the relationship of aberrant protein expression. Dr. Moritz is active in teaching and dissemination of proteomics technologies fosters education exchanges and create forums for collaborative relationships centered on the human proteome.


Quantitative Proteomics in Wellness and Disease Settings
Institute for Systems Biology, Seattle, WA, USA

The convergence of advances in systems medicine, big data analysis, individual measurement devices, and consumer-activated social networks has led to a vision of healthcare that is predictive, preventive, personalized, and participatory (P4), also known as ‘precision medicine’. In order to understand the basis of wellness and disease, we have pursued a global and holistic approach termed ‘systems medicine’. The defining feature of systems medicine is the collection of diverse longitudinal data for each individual. These data sets can be used to unravel the complexity of human biology and disease by assessing both genetic and environmental determinants of health and their interactions. We refer to such data as personal, dense, dynamic data clouds: personal, because each data cloud is unique to an individual; dense, because of the high number of measurements; and dynamic, because we monitor longitudinally. The genome provides the basis of which predictions of wellness can be made and according to population statistics, propensities of disease can be assumed. Of all the measurements, proteins are indicators of the current health status and their reliable, comprehensive and quantitative measurement is key to unlocking the trajectories of wellness.
To perform large scale quantitative proteomic experiments over hundreds of samples with robust operation, reproducibility across different complex matrices, a system that is well characterized both in terms of data collection and data analysis is paramount. I will discuss our methods in attaining high accuracy and signal stability in label free proteomics enabling the processing of many hundreds of samples in an automated unattended operation. Our latest methods in SWATH-MS operation and data analysis with superior higher performance characteristics and steps to achieve these types of results and operational specifics for wellness and disease studies will be discussed.