| Light‐absorbing properties of ambient black carbon and brown carbon from fossil fuel and biomass burning sources RM Healy, JM Wang, CH Jeong, AKY Lee, MD Willis, E Jaroudi, ... Journal of Geophysical Research: Atmospheres 120 (13), 6619-6633, 2015 | 121 | 2015 |
| Single particle diversity and mixing state measurements RM Healy, N Riemer, JC Wenger, M Murphy, M West, L Poulain, ... Atmospheric Chemistry and Physics 14 (12), 6289-6299, 2014 | 66 | 2014 |
| Single-particle speciation of alkylamines in ambient aerosol at five European sites RM Healy, GJ Evans, M Murphy, B Sierau, J Arndt, E McGillicuddy, ... Analytical and bioanalytical chemistry 407, 5899-5909, 2015 | 48 | 2015 |
| Predicting human health from biofluid-based metabolomics using machine learning ED Evans, C Duvallet, ND Chu, MK Oberst, MA Murphy, I Rockafellow, ... Scientific reports 10 (1), 17635, 2020 | 20 | 2020 |
| Predicting hygroscopic growth using single particle chemical composition estimates RM Healy, GJ Evans, M Murphy, Z Jurányi, T Tritscher, M Laborde, ... Journal of Geophysical Research: Atmospheres 119 (15), 9567-9577, 2014 | 20 | 2014 |
| Comparative proteomic analysis highlights metabolic dysfunction in α-synucleinopathy S Sarkar, MA Murphy, EB Dammer, AL Olsen, S Rangaraju, E Fraenkel, ... NPJ Parkinson's disease 6 (1), 40, 2020 | 18 | 2020 |
| Single cell metabolism: current and future trends A Ali, S Davidson, E Fraenkel, I Gilmore, T Hankemeier, JA Kirwan, ... Metabolomics 18 (10), 77, 2022 | 13 | 2022 |
| Efficiently predicting high resolution mass spectra with graph neural networks M Murphy, S Jegelka, E Fraenkel, T Kind, D Healey, T Butler International Conference on Machine Learning, 25549-25562, 2023 | 12 | 2023 |
| Self-supervised learning of cell type specificity from immunohistochemical images M Murphy, S Jegelka, E Fraenkel Bioinformatics 38 (Supplement_1), i395-i403, 2022 | 6 | 2022 |
| Interim report of the GAA Healthy Club Project A Lane, M Murphy, A Donohoe Accessed October, 2015 | 2 | 2015 |
| Systems and methods for identifying precursor and product ion pairs in scanning SWATH data G Ivosev, NG Bloomfield, M Murphy, SA Tate US Patent 10,651,019, 2020 | 1 | 2020 |
| Machine Learning Methods for High Throughput Biological Data MA Murphy Massachusetts Institute of Technology, 2024 | | 2024 |
| Multi-omics characterization of human kidneys identifies cPLA2-arachidonic acid metabolism as a potential driver of inflammation E Asowata, S Romoli, J Tan, S Hoffmann, M Huang, F Krause, B Jenkins, ... | | 2022 |
| Neural Network Prediction of Peptide Fragmentation Mass Spectra M Murphy University of Toronto, 2017 | | 2017 |
| Systems and Methods For Identifying Precursor and Product Ion Pairs in Scanning Swath Data G Ivosev, N Bloomfield, M Murphy, S Tate US Patent App. 62/366,526, 2016 | | 2016 |
| Using Scanning SWATH® Windows to Improve Both Quantitative and Qualitative Data Over Conventional SWATH and IDA Methodologies M Murphy, G Ivosev, S Tate, Y Kang, N Bloomfield Conference of the American Society of Mass Spectrometry, 2016 | | 2016 |
| Learning representations from mass spectra for peptide property prediction M Murphy, K Yang, S Jegelka, E Fraenkel | | |
Robert M. HealyOntario Ministry of the EnvironmentDirección de correo verificada de ontario.ca
