Home Cytometry History Individual Histories Robert F. Murphy

Robert F. Murphy

Robert F. Murphy is currently the Ray and Stephanie Lane Chair in Computational Biology, Professor of Biological Sciences, Biomedical Engineering, and Machine Learning, and Director (with Jelena Kovacevic) of the Center for Biomedical Image Informatics at Carnegie Mellon. He also is Director (with Ivet Bahar) of the joint CMU-Pitt Ph.D. Program in Computational Biology. The focus of his career has been on combining fluorescence-based cell measurement methods with quantitative and computational methods. In the 1980’s, his group at Carnegie Mellon did extensive work on the application of flow cytometry to analyze endocytic membrane traffic and on the application of computational methods to flow cytometry data. Notable achievements during this period include proposing (with Tom Chused) the Flow Cytometry Standard (FCS) data file format and the first work on Single Organelle Flow Analysis to analyzing individual endocytic organelles.

In the mid 1990’s, his group pioneered the application of machine learning methods to high-resolution fluorescence microscope images depicting subcellular location patterns. This work led to the development of the first systems for automatically recognizing all major organelle patterns in 2D and 3D images. His group also created and maintains the Protein Subcellular Location Image Database, the first publicly available, open source database and analysis tools for high-resolution location analysis, and the Subcellular Location Image Finder, the first system for extracting information from both image and text in figures from biomedical literature. With B.S. Manjunath at the University of California, Santa Barbara he is leading a major effort to create a new multi-institution, NSF-funded $9.4 million program in bioimage informatics that is bridging biology, cytometry, engineering and computer science. This led to the creation of the Center for Bioimage Informatics, which Murphy founded in 2003 with Jelena Kovacevic, as a focal point for research on the automated generation of biological knowledge from images. Murphy’s group is responsible for providing image informatics tools for the MBIC TCNP and for providing structured, image-based information on subcellular location for the National Center for Integrative Biomedical Informatics (led by Brian Athey at the University of Michigan).

Dr. Murphy earned an A. B. in Biochemistry from Columbia College in 1974 and a Ph.D. in Biochemistry from the California Institute of Technology in 1980. He was a Damon Runyon-Walter Winchell Cancer Foundation postdoctoral fellow with Dr. Charles R. Cantor at Columbia University from 1979 through 1983, after which he became an Assistant Professor of Biological Sciences at Carnegie Mellon University. He received a Presidential Young Investigator Award from the National Science Foundation in 1983 and was named a Fellow of the American Institute for Medical and Biological Engineering and a Senior Member of IEEE in 2007. He has served as Chair of the NIH Biological Data Modeling and Analysis study section, and co-edited two special journal issues on Cell and Molecular Imaging. He has authored or co-authored over 140 scientific papers and is currently on the editorial boards of the Journal of Proteome Research and Cytometry Part A. He is President-elect of the International Society for Analytical Cytology.

Mario Roederer as a Ph.D. student in Bob Murphy’s group in the Center for Fluorescence Research in Biomedical Sciences at Carnegie Mellon University.

Bob’s first Ph.D. student was Mario Roederer, who worked on analysis of endocytic membrane traffic using flow cytometry and did extensive work on computational tools for acquiring and analyzing flow cytometry data. Mario did his postdoctoral work with Len Herzenberg at Stanford University, and is the world’s leading developer and practioner of polychromatic flow cytometry. He is currently the Director of the Flow Cytometry Facility at the Vaccine Research Laboratory at the National Institute of Allergy and Infectious Diseases. Other students who did their undergraduate or graduate research in his lab include Cynthia (Corley) Mastick (Associate Professor of Biochemistry at the University of Nevada, Reno), Robert Bowser (Associate Professor of Pathology at the University of Pittsburgh), Robert Mays (Director of Cell Biology at Athersys, Inc.), and Michael Boland (Assistant Professor of Ophthalmology at Johns Hopkins University).

Selected cytometry publications authored or co-authored by Robert F. Murphy

  1. R.F. Murphy, E.D. Jorgensen and C.R. Cantor (1982). Kinetics of Histone Endocytosis in Chinese Hamster Ovary Cells: A Flow Cytofluorometric Analysis. J. Biol. Chem. 257:1695-1701.
  2. R.F. Murphy, S. Powers and C.R. Cantor (1984). Endosome pH Measured in Single Cells by Dual Fluorescence Flow Cytometry: Rapid Acidification of Insulin to pH 6. J. Cell Biol. 98:1757-1762. [105 citations according to ISI as of September 2006]
  3. R.F. Murphy and T.M. Chused (1984). A Proposal for a Flow Cytometric Data File Standard. Cytometry 5:553-555.
  4. R.F. Murphy (1985). Analysis and Isolation of Endocytic Vesicles by Flow Cytometry and Sorting: Demonstration of Three Kinetically Distinct Compartments Involved in Fluid-Phase Endocytosis. Proc. Natl. Acad. Sci. USA 82:8523-8526. [49 citations according to ISI as of September 2006]
  5. M. Roederer and R.F. Murphy (1986). Cell-By-Cell Autofluorescence Correction for Low Signal-to-Noise Systems: Application to EGF Endocytosis by 3T3 Fibroblasts. Cytometry 7:558-565. [41 citations according to ISI as of September 2006]
  6. C.C. Cain, D.M. Sipe and R.F. Murphy (1989). Regulation of Endocytic pH by the Na+ /K+-ATPase in Living Cells. Proc. Natl. Acad. Sci. USA 86:544-548. [125 citations according to ISI as of September 2006]
  7. M.V. Boland, M.K. Markey and R.F. Murphy (1998). Automated Recognition of Patterns Characteristic of Subcellular Structures in Fluorescence Microscopy Images. Cytometry 33:366-375.
  8. M.V. Boland and R.F. Murphy (2001). A Neural Network Classifier Capable of Recognizing the Patterns of all Major Subcellular Structures in Fluorescence Microscope Images of HeLa Cells. Bioinformatics 17:1213-1223.
  9. K. Huang and R.F. Murphy (2004). Boosting accuracy of automated classification of fluorescence microscope images for location proteomics. BMC Bioinformatics 5:78.
  10. S.C. Chen, and R.F. Murphy (2006). A Graphical Model Approach to Automated Classification of Protein Subcellular Location Patterns in Multi-Cell Images. BMC Bioinformatics 7:90.
  11. X. Chen, M. Velliste, and R.F. Murphy (2006). Automated Interpretation of Subcellular Patterns in Fluorescence Microscope Images for Location Proteomics. Cytometry 69A:631-640.