Prof. Eitan Rubin

Prof. Eitan Rubin Profile

Associate Professor
Ph.D., 1999

Researcher

Department : Shraga Segal Department of Microbiology, Immunology and Genetics
Room :
Phone :
Email : erubin@bgu.ac.il
Office Hours :  
bio-informatics, genetics, data-mining, Precision Cancer Medicine, Precision Oncology, Data Sciences

Education

  • 1993 – 2001 Weizmann Institute of Science, Ph.D in Plant Sciences with Prof. A. Levy. Thesis title: "The evolution of the Ac/Ds transposon family". 1992 - 1993 Weizmann Institute of Science, M.Sc in Plant Sciences with Prof. A. Levy. Switched to direct Ph.D. course. 1989 - 1992 Ben Gurion University. B.Sc. in Biology. (with Distinction).

Research Interests

  • Bio-informatics, systems biology, medical informatics

Research Projects

Breast cancer recurrence

Gender Differences and Cancer

Research Topics

  • Sources of human phenotypic variation (with a special emphasis on drug response)
  • Cancer stratification (precision oncology)

Major expertise and techniques in the lab

  • Data mining using supervised and unsupervised methods
  • Next-generation sequence analysis (DNA/RNA/Other)
  • General bioinformatics methods, with a focus on nucleic acids

Publications and funding summary / representative publications and grants

  • Rodon et. al. (2019) "Genomic and transcriptomic profiling expands precision cancer medicine: the WINTHER trial". Nature Medicine 25:751758 
  • Gordon, M., Moser, A. and Rubin, E. (2012) “ Unsupervised Analysis of Classical Biomedical Markers: Robustness and Medical Relevance of Patient Clustering Using Bioinformatics Tools”. Plos One, 7(3): e29578

Existing collaborations

  • Angel Porgador – Early cancer diagnosis
  • The WIN consortium - Precision Oncology and clinical trials

Suggested multi-disciplinary research project / research focus topics

  • Personalized medicine: finding new diagnostic tools
  • Cancer genomics: evaluating the contribution of specific pathways or genes

Looking for expertise / project

  • Genetic research of cancer
  • Precision Oncology
  • Machine learning

Additional links