Dan Ruderman, PhD
Assistant Professor of Research Medicine
310 228 6400 | dan.ruderman@ellison.usc.edu
Dan is an Assistant Professor of Research Medicine at the Keck School of Medicine of USC and the Lawrence J. Ellison Institute for Transformative Medicine. He received his doctorate in theoretical physics from the University of California at Berkeley, followed by postdoctoral research at Cambridge University, USC, and the Salk Institute. He then continued his scientific research in the industrial setting, first in solid tumor target discovery through integrative genomics at Berlex Biosciences, and then in proteomic biomarker discovery at Applied Minds. Dan was Founding Scientist at Applied Proteomics, a biomarker company spun out from Applied Minds in 2007. He joined the Ellison Institute in 2011 where his research focuses on signaling dynamics in cancer cells and systems biology interpretations of high-dimensional cancer assays, such as gene expression, proteomics, and autoantibodies.  

Research Focus

Intracellular dynamics
Intratumor heterogeneity
Digital pathology
Machine learning and statistical methods 

Mayada Aljehani, DrPH
Ellen Emerson
Bethany Haliday
Edwin Heredia, PhD
Naim Matasci, PhD
Katherin Patsch, PhD
Ren Sun, MSc
Harish Sura, MS
Nolan Ung, PhD
Greg Zapotoczny, PhD

Education

BA

1989 Physics – University of California, Berkeley, CA  

PhD

1993 Physics – University of California, Berkeley, CA  

Fellowship

1993-1995 Postdoctoral Fellow – The Physiological Laboratory, Cambridge University, UK
1995-1996 Department of Biomedical Engineering – USC, Los Angeles, CA
1996-1998 Postdoctoral Fellow – Sloan Center for Theoretical Neuroscience, The Salk Institute

Awards

Sloan Foundation: Postdoctoral Fellowship, 1996-1998 
National Science Foundation/ North Atlantic Treaty Organization: Postdoctoral Fellowship, 1994 
Fannie and John Hertz Foundation: Fellowship, 1989-1993 
National Science Foundation: Fellowship, 1993 
Phi Beta Kappa: Elected Member, 1988 
 
National Academy of Inventors: Elected Member, 2018

Selected Publications

Rawat RR, Ruderman D, Macklin P, Rimm DL, Agus DB. Correlating nuclear morphometric patterns with estrogen receptor status in breast cancer pathologic specimens. NPJ Breast Cancer. 2018 Sep 4;4:32. View in: PubMed
Ruderman D. The emergence of dynamic phenotyping. Cell Biol. Toxicol. 2017 Dec;33(6):507-509. View in: PubMed  
Patsch K, Chiu CL, Engeln M, Agus DB, Mallick P, Mumenthaler SM, Ruderman D. Single cell dynamic phenotyping. Sci Rep. 2016 Oct 6;6:34785. View in: PubMed
Ruderman, Daniel L.; Bialek, William. Statistics of natural images: scaling in the woods. Physical Review Letters, v 73, n 6, p 814, Aug 8 1994. 
Ruderman, Daniel L.; Cronin, Thomas W.; Chiao, Chuan-Chin. Statistics of cone responses to natural images: implications for visual coding. Journal of the Optical Society of America A: Optics and Image Science, and Vision, v 15, n 8, p 2036, Aug 1998. 
Ruderman, Daniel L. Origins of scaling in natural images. Vision Research. 1997;37(23):3385-3398. View: Here
Mel BW, Ruderman DL, Archie KA. Translation-invariant orientation tuning in visual “complex” cells could derive from intradendritic computations. J Neurosci. 1998 Jun 1; 18(11):4325-34. View in: PubMed
Kani K, Malihi PD, Jiang Y, Wang H, Wang Y, Ruderman DL, Agus DB, Mallick P, Gross ME. Anterior gradient 2 (AGR2): blood-based biomarker elevated in metastatic prostate cancer associated with the neuroendocrine phenotype. Prostate. 2013 Feb 15; 73(3):306-15. View in: PubMed
D L Ruderman.  Designing receptive fields for highest fidelity. Network: Computation in Neural Systems. 1994;5(2):147-155. 
Turiel, Antonio (Depto. de Fis. Teórica, Univ. Autónoma de Madrid, 28049 Madrid, Spain); Parga, Néstor; Ruderman, Daniel L.;Cronin, Thomas W.  Multiscaling and information content of natural color images. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, v 62, n 1 B, p 1138-1148, July 2000. 
Dan Ruderman, PhD
Assistant Professor of Research Medicine
310 228 6400
dan.ruderman@ellison.usc.edu
Dan is an Assistant Professor of Research Medicine at the Keck School of Medicine of USC and the Lawrence J. Ellison Institute for Transformative Medicine. He received his doctorate in theoretical physics from the University of California at Berkeley, followed by postdoctoral research at Cambridge University, USC, and the Salk Institute. He then continued his scientific research in the industrial setting, first in solid tumor target discovery through integrative genomics at Berlex Biosciences, and then in proteomic biomarker discovery at Applied Minds. Dan was Founding Scientist at Applied Proteomics, a biomarker company spun out from Applied Minds in 2007. He joined the Ellison Institute in 2011 where his research focuses on signaling dynamics in cancer cells and systems biology interpretations of high-dimensional cancer assays, such as gene expression, proteomics, and autoantibodies.  

Research Focus

Intracellular dynamics
Intratumor heterogeneity
Digital pathology
Machine learning and statistical methods 


Mayada Aljehani, DrPH
Ellen Emerson
Bethany Haliday
Edwin Heredia, PhD

Naim Matasci, PhD
Katherin Patsch, PhD
Ren Sun, MSc
Harish Sura, MS
Nolan Ung, PhD
Greg Zapotoczny, PhD

Education

BA

1989 Physics – University of California, Berkeley, CA  

PhD

1993 Physics – University of California, Berkeley, CA  

Fellowship

1993-1995 Postdoctoral Fellow – The Physiological Laboratory, Cambridge University, UK
1995-1996 Department of Biomedical Engineering – USC, Los Angeles, CA
1996-1998 Postdoctoral Fellow – Sloan Center for Theoretical Neuroscience, The Salk Institute

Awards

  • Sloan Foundation: Postdoctoral Fellowship, 1996-1998
  • National Science Foundation/ North Atlantic Treaty Organization: Postdoctoral Fellowship, 1994
  • Fannie and John Hertz Foundation: Fellowship, 1989-1993
  • Phi Beta Kappa: Elected Member, 1988
  • National Academy of Inventors: Elected Member, 2018 

Selected Publications

Rawat RR, Ruderman D, Macklin P, Rimm DL, Agus DB. Correlating nuclear morphometric patterns with estrogen receptor status in breast cancer pathologic specimens. NPJ Breast Cancer. 2018 Sep 4;4:32. View in: PubMed
Ruderman D. The emergence of dynamic phenotyping. Cell Biol. Toxicol. 2017 Dec;33(6):507-509. View in: PubMed  
Patsch K, Chiu CL, Engeln M, Agus DB, Mallick P, Mumenthaler SM, Ruderman D. Single cell dynamic phenotyping. Sci Rep. 2016 Oct 6;6:34785. View in: PubMed
Ruderman, Daniel L.; Bialek, William. Statistics of natural images: scaling in the woods. Physical Review Letters, v 73, n 6, p 814, Aug 8 1994. 
Ruderman, Daniel L.; Cronin, Thomas W.; Chiao, Chuan-Chin. Statistics of cone responses to natural images: implications for visual coding. Journal of the Optical Society of America A: Optics and Image Science, and Vision, v 15, n 8, p 2036, Aug 1998. 
Ruderman, Daniel L. Origins of scaling in natural images. Vision Research. 1997;37(23):3385-3398. View: Here
Mel BW, Ruderman DL, Archie KA. Translation-invariant orientation tuning in visual “complex” cells could derive from intradendritic computations. J Neurosci. 1998 Jun 1; 18(11):4325-34. View in: PubMed
Kani K, Malihi PD, Jiang Y, Wang H, Wang Y, Ruderman DL, Agus DB, Mallick P, Gross ME. Anterior gradient 2 (AGR2): blood-based biomarker elevated in metastatic prostate cancer associated with the neuroendocrine phenotype. Prostate. 2013 Feb 15; 73(3):306-15. View in: PubMed
D L Ruderman.  Designing receptive fields for highest fidelity. Network: Computation in Neural Systems. 1994;5(2):147-155. 
Turiel, Antonio (Depto. de Fis. Teórica, Univ. Autónoma de Madrid, 28049 Madrid, Spain); Parga, Néstor; Ruderman, Daniel L.;Cronin, Thomas W.  Multiscaling and information content of natural color images. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, v 62, n 1 B, p 1138-1148, July 2000.