Robert Murphy
Ray and Stephanie Lane Professor of Computational Biology Emeritus
Computational Biology
Orcid identifier0000-0003-0358-901X (opens in a new tab)
- Ray and Stephanie Lane Professor of Computational Biology EmeritusComputational Biology
BIO
obert F. Murphy is the Ray and Stephanie Lane Professor of Computational Biology at Carnegie Mellon University. He also is Professor of Biological Sciences, Biomedical Engineering, and Machine Learning. He was Founding Head of the Computational Biology Department (formerly the Ray and Stephanie Lane Center for Computational Biology) in the School of Computer Science at Carnegie Mellon from 2009 to 2020. He was also Founding Director (with Ivet Bahar) of the Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology. He is an Honorary Professor of Biology at the Albert Ludwig University of Freiburg, Germany, was named as the first External Senior Fellow of the School of Life Sciences in the Freiburg Institute for Advanced Studies, and was the recipient of an Alexander von Humboldt Foundation Senior Research Award. He is a Fellow of the Institute of Electrical and Electronic Engineers IEEE) and the American Institute for Medical and Biological Engineering, and served as President of the International Society for Advancement of Cytometry. He was the first full-term chair of the Biodata Management and Analysis Study Section of the National Institutes of Health, and was a member of the National Advisory General Medical Sciences Council, and the National Institutes of Health Council of Councils.
Dr. Murphy has received research grants from the National Institutes of Health, the National Science Foundation, the American Cancer Society, the American Heart Association, the Arthritis Foundation, and the Rockefeller Brothers Fund. He has co-edited two books and three special journal issues on cell imaging, and has published over 200 research papers.
Dr. Murphy’s career has centered on combining fluorescence-based cell measurement methods with quantitative and computational methods. His group at Carnegie Mellon did extensive work on the application of flow cytometry to analyze endocytic membrane traffic beginning in the early 1980’s. This work included the first (1) measurements of kinetics of rapid acidification of endocytosed material in early endosomes, (2) measurements of the kinetics of exposure of endocytosed material to hydrolytic enzymes in early endosomes in living cells, (3) demonstration in living cells of the regulation of early endosomal pH by the sodium, potassium ATPase, and (4) analysis and isolation of endocytic compartments by flow cytometry and sorting.
In the mid 1990’s, his group pioneered the application of machine learning methods to high-resolution fluorescence microscope images depicting subcellular location patterns, and was the first to demonstrate superior machine performance in interpreting diverse patterns in biological images compared to visual interpretation. In 2003 he and B.S. Manjunath obtained major cooperative grants from the National Science Foundation to found Centers for Bioimage Informatics at Carnegie Mellon and the University of California, Santa Barbara. His group’s work over the past 20 years led to the development of the first (1) systems for automatically recognizing all major organelle patterns in 2D and 3D images, (2) system for building generative models of subcellular organization directly from images, (3) systems for calculating the fraction of proteins in different organelles using both supervised and unsupervised unmixing methods, and (4) systems for automatically recognizing all major subcellular patterns in tissue images. His current research interests include machine learning of image-derived models of cell organization, automated detection of protein location changes during oncogenesis, and active machine learning approaches to experimental biology.
Dr. Murphy’s leadership experience includes developing the first formal undergraduate program in computational biology in 1987 and founding the Merck Computational Biology and Chemistry program at Carnegie Mellon in 1999. These programs were important forerunners to the 2005 establishment of the joint Ph.D. program in computational biology with the University of Pittsburgh. Under his and Dr. Bahar’s leadership, this program was chosen as one of only ten awardees through Phase I of the HHMI-NIBIB Interfaces Initiative and was one of only eight to receive a Phase II training grant from the National Institute of Biomedical Imaging and Bioengineering. Under Dr. Murphy’s leadership, the Lane Center for Computational Biology was granted department status within the School of Computer Science in September 2009.
Dr. Murphy was a Cofounder and Board Member of Quantitative Medicine, LLC which was purchased by Predictive Oncology, Inc. in 2020.
Dr. Murphy received an A.B. in Biochemistry from Columbia College and a Ph.D. in Biochemistry from the California Institute of Technology. He was a Damon Runyon-Walter Winchell Cancer Foundation Postdoctoral Fellow with Dr. Charles Cantor at Columbia University.
Dr. Murphy has received research grants from the National Institutes of Health, the National Science Foundation, the American Cancer Society, the American Heart Association, the Arthritis Foundation, and the Rockefeller Brothers Fund. He has co-edited two books and three special journal issues on cell imaging, and has published over 200 research papers.
Dr. Murphy’s career has centered on combining fluorescence-based cell measurement methods with quantitative and computational methods. His group at Carnegie Mellon did extensive work on the application of flow cytometry to analyze endocytic membrane traffic beginning in the early 1980’s. This work included the first (1) measurements of kinetics of rapid acidification of endocytosed material in early endosomes, (2) measurements of the kinetics of exposure of endocytosed material to hydrolytic enzymes in early endosomes in living cells, (3) demonstration in living cells of the regulation of early endosomal pH by the sodium, potassium ATPase, and (4) analysis and isolation of endocytic compartments by flow cytometry and sorting.
In the mid 1990’s, his group pioneered the application of machine learning methods to high-resolution fluorescence microscope images depicting subcellular location patterns, and was the first to demonstrate superior machine performance in interpreting diverse patterns in biological images compared to visual interpretation. In 2003 he and B.S. Manjunath obtained major cooperative grants from the National Science Foundation to found Centers for Bioimage Informatics at Carnegie Mellon and the University of California, Santa Barbara. His group’s work over the past 20 years led to the development of the first (1) systems for automatically recognizing all major organelle patterns in 2D and 3D images, (2) system for building generative models of subcellular organization directly from images, (3) systems for calculating the fraction of proteins in different organelles using both supervised and unsupervised unmixing methods, and (4) systems for automatically recognizing all major subcellular patterns in tissue images. His current research interests include machine learning of image-derived models of cell organization, automated detection of protein location changes during oncogenesis, and active machine learning approaches to experimental biology.
Dr. Murphy’s leadership experience includes developing the first formal undergraduate program in computational biology in 1987 and founding the Merck Computational Biology and Chemistry program at Carnegie Mellon in 1999. These programs were important forerunners to the 2005 establishment of the joint Ph.D. program in computational biology with the University of Pittsburgh. Under his and Dr. Bahar’s leadership, this program was chosen as one of only ten awardees through Phase I of the HHMI-NIBIB Interfaces Initiative and was one of only eight to receive a Phase II training grant from the National Institute of Biomedical Imaging and Bioengineering. Under Dr. Murphy’s leadership, the Lane Center for Computational Biology was granted department status within the School of Computer Science in September 2009.
Dr. Murphy was a Cofounder and Board Member of Quantitative Medicine, LLC which was purchased by Predictive Oncology, Inc. in 2020.
Dr. Murphy received an A.B. in Biochemistry from Columbia College and a Ph.D. in Biochemistry from the California Institute of Technology. He was a Damon Runyon-Walter Winchell Cancer Foundation Postdoctoral Fellow with Dr. Charles Cantor at Columbia University.
ACADEMIC POSITIONS
- External Senior FellowAlbert Ludwigs University, Freiburg, Germany2008 - present
- Honorary ProfessorAlbert Ludwigs University, Freiburg, Germany2008 - present
- HeadCarnegie Mellon University, Computational Biology Department, Pittsburgh, USA1 Jan 2007 - present
- Professor of Machine LearningCarnegie Mellon University, Pittsburgh, USA1 Jan 2006 - present
- Professor of Biological Sciences and Biomedical EngineeringCarnegie Mellon University, Pittsburgh, United States1 Jan 2003 - present
- Faculty of Biomedical EngineeringCarnegie Mellon University, Pittsburgh, United States1 Jan 1998 - 1 Jan 2002
- Undergraduate Research AdvisorCarnegie Mellon University, Dept. of Biological Sciences, Pittsburgh, United States1 Jan 1996 - 1 Jan 2000
- Visiting Associate Professor of BiologyJohns Hopkins University, Baltimore, United States1 Jan 1994 - present
- Assistant Professor of Biological SciencesCarnegie Mellon University, Pittsburgh, United States1 Jan 1983 - 1 Jan 1989
NON-ACADEMIC POSITIONS
- Founder/Board MemberQuantitative Medicine LLC, United States2012 - present
DEGREES
- Ph.D BiochemistryCalifornia Institute of Technology, Pasadena, United States1974 - 1979
- B.A. BiochemistryColumbia University, New York, United States1971 - 1974
POSTGRADUATE TRAINING
- Postdoctoral Research AssociateColumbia University, Departments of Chemistry and Human Genetics, New York, United States1979 - 1983Postdoctoral ResearchSupervised by Cantor
CAMPUS
- Remote Work Location
SUSTAINABLE DEVELOPMENT GOALS
- 14 Life Below Water
- 3 Good Health and Well Being
- 15 Life on Land