About the Principal Investigator

Michael MacCoss

NIH Biosketch

Brief Research Biography: Michael MacCoss has been working with mass spectrometry instrumentation since 1994. He became interested in biomedical applications during summer internships at Merck Research Laboratories in 1995 and 1996. In 2001, he completed a Ph.D. in Analytical Chemistry with Professor Dwight Matthews developing stable isotope and mass spectrometry methodologies for measuring human amino acid and protein metabolism. As a postdoctoral fellow with proteomics pioneer John R. Yates III at The Scripps Research Institute, Dr. MacCoss developed methodologies and software for characterizing post-translational modifications and quantitative analysis of complex protein mixtures.

Dr. MacCoss joined the University of Washington in 2004 as an Assistant Professor of Genome Sciences and was promoted to Professor in 2014. Recognizing that software was a major bottleneck limiting quantitative accuracy and reproducibility in proteomics, Dr. MacCoss established a software engineering effort with Brendan MacLean. This effort produced Skyline, a widely-adopted open-source platform for quantitative mass spectrometry that has become essential for workflows across the field, and Panorama, a web-based repository for mass spectrometry data sharing and collaboration. The laboratory’s software is noted for its robustness, versatility, extensive support, and user friendliness. The MacCoss lab has also contributed to key computational tools in the field through close collaborations, including but not limited to the development of Percolator with the Noble lab for semi-supervised learning of peptide identification and Comet with Jimmy Eng for sequence database searching. Throughout his career, Dr. MacCoss has been a strong advocate for mass spectrometry-based quantitative proteomics, championing the development and adoption of targeted proteomics and data-independent acquisition (DIA) methods to improve the rigor, reproducibility, and clinical relevance of protein measurements. Beyond software development, the MacCoss lab has made significant methodological advances in data-independent acquisition, targeted proteomics, sample preparation, and instrumentation, applied to aging, cancer, cardiovascular disease, diabetes, and neurodegeneration.

His contributions have been recognized with several awards, including the ASMS Research Award (2004), the Presidential Award for Scientists and Engineers (PECASE, 2007), the Biemann Medal from the American Society for Mass Spectrometry (2015), the HUPO Award for Discovery in Proteomics Sciences (2016), and the Donald F. Hunt Distinguished Contribution in Proteomics Award from US HUPO (2026). The MacCoss lab’s research operates at the intersection of biochemistry, instrumentation, engineering, computer science, and statistics, with sustained focus on advancing quantitative proteomics capabilities.