Imperial College London


Faculty of EngineeringDepartment of Chemical Engineering




+44 (0)20 7594 5589p.dimaggio Website




218ACE ExtensionSouth Kensington Campus





Date Role
2015- Senior Lecturer, Department of Chemical Engineering, Imperial College London
2012-2015 Lecturer, Department of Chemical Engineering, Imperial College London
2010-2012 NIH/NRSA Postdoctoral Fellow, Department of Molecular Biology, Princeton University
2004-2010 PhD in Chemical Engineering, Department of Chemical Engineering, Princeton University

Research Interests 

The DiMaggio Lab is interested in the development and application of innovative experimental and computational platforms for characterizing chromatin-associated proteins and how their interactions and post-translational modifications cooperatively regulate nuclear processes, such as gene expression.  At the center of our research program is liquid chromatography tandem mass spectrometry (LC-MS/MS), and our work contributes to this field on two fronts:

1. The application of fundamental chemical engineering principles towards the design, modeling and optimization of separation processes and analyte detection.

2.  The development of optimization-based computational tools for robustly interpretting novel sources of LC-MS/MS data.



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Selected Publications

Journal Articles

LeRoy G, DiMaggio PA, Chan EY, et al., 2013, A quantitative atlas of histone modification signatures from human cancer cells, Epigenetics & Chromatin, Vol:6, ISSN:1756-8935

Wu Y, DiMaggio PA, Perlman DH, et al., 2013, Novel Phosphorylation Sites in the S. cerevisiae Cdc13 Protein Reveal New Targets for Telomere Length Regulation, Journal of Proteome Research, Vol:12, ISSN:1535-3893, Pages:316-327

DiMaggio PA, Young NL, Baliban RC, et al., 2009, A Mixed-Integer Linear Optimization Framework for the Identification and Quantification of Targeted Post-translational Modifications of Highly-Modified Proteins using ETD Tandem Mass Spectrometry, Molecular and Cellular Proteomics, Vol:11, Pages:2527-2543

DiMaggio PA, McAllister SR, Floudas CA, et al., 2008, Biclustering via Optimal Re-ordering of Data Matrices in Systems Biology: Rigorous Methods and Comparative Studies, Bmc Bioinformatics

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