We study the molecular network mechanisms that are the core difference between a healthy tissue and a sick tissue. We study transcriptional network alterations associated with the tumor phenotype and with specific tumor phenotypes. We focus on the subnetwrok as the unit that drives chance. In the systems we study,

we see how this shift in viewpoint assists in a better understaing of the system. The experiments we perform are aimed at genome-wide, high-throughput, analyses platforms. The data we obtain is analyzed using the tools we and others develope to cope with this genome-wide, network entangled, complexity.


Dr. Sol Efroni

Senior Lecturer, PI

Dr. Alona Zilberberg

Lab Manager


We are looking for excellent postdocs. Applicants with diverse backgrounds are wellcome to contact us through the “Contact” page. Ph.Ds with experimental background or computatinal background may apply.

  • team3

    Rotem Ben-Hamo

    Ph.D. student

  • team8

    Rivka Cashman

    Ph.D. student

  • team5

    Miri Gordin

    Ph.D. student

  • team6

    Dror Hibsh

    Ph.D. student

  • team10

    Hagit Philip

    Ph.D. student

  • Omer Ben-Zvi

    M.Sc. student

  • Batel Luzun

    M.Sc. student

  • team9

    Renena Kozol

    M.Sc. student

  • team11

    Ido Sloma

    M.Sc. student

  • Lital Tybloom

    M.Sc. student



We developed a method to use pathway knowledge to find out properties of biological samples. We mainly use gene expression data, but recently added protein level data and genomic data to help us find out basic mechanisms in tumor formation.

We use the pathway knowledge on top gene and protein information to perform diagnosis and prognosis of samples from cancer patients. The method works very well, as can be seen in this figure and in the paper.

We are then able to find the pathways most critical to make that diagnosis. By being of higher importance in diagnosis, we assume they are also more crticial in phenotypic behavior.

The Nano Technology Complex

The new Nano technology complex at Bar Ilan University, in which the Systems BioMedicine lab resides, is a state of the art facility, reaching its final stages of completion. The lab is at the 8th floor of this complex, which hosts labs from Biology, Chemistry and Physics.

A further proof to the importance of pathways and the power of the metric is with the ability to stratify patient groups according to survival. The pathway metric does exceptionally well in this:

A further proof to the importance of pathways and the power of the metric is with the ability to stratify patient groups according to survival. The pathway metric does exceptionally well in this:


Reactive Animation is the combination between tools to analyze and design reactive systems and tools to animate display front end interfaces.

In the examples you see below, the tool we used to analyze reactive behavior is Rhapsody and the tool we used for the animated front-end is Flash from Adobe.

The examples show screen captures from a simulation we built to learn about thymic development in the mammalian thymus.

Here are examples from the simulation we built for thymocyte development in the thymic lobule:



publication All Publications




Heat acclimation memory: Do the kinetics of the de-acclimated transcriptome predispose to rapid re-acclimation and cytoprotection?

J Appl Physiol
Tetievsky A, Assayag M, Ben-Hamo R, Efroni S, Cohen G, Abbas A, Horowitz M.

Shift in GATA3 Functions, and GATA3 Mutations, Control Progression and Clinical Presentation in Breast Cancer

Breast Cancer Research
Helit Cohen, Rotem Ben-Hamo, Moriah Gidoni, Ilana Yitzhaki, Renana Kozol, Alona Zilberberg and Sol Efroni

PhenoNet: Identification of key networks associated with disease phenotype

Rotem Ben-Hamo, Moriah Cohen-Gidoni, Sol Efroni

SENP5 mediates breast cancer invasion via a TGFβRI SUMOylation cascade

Rivki Cashman , Helit Cohen , Rotem Ben-Hamo , Alona Zilberberg, Sol Efroni

MicroRNA Regulation of Molecular Pathways as a generic mechanism and as a Core Disease Phenotype

Rotem Ben-Hamo, Sol Efroni



MicroRNA-Gene Association As a Prognostic Biomarker in Cancer Exposes Disease Mechanisms

PLoS Comput Biol 9(11): e1003351
Ben-Hamo R, Efroni S

Network as biomarker: Quantifying transcriptional co-expression to stratify cancer clinical phenotypes.

Systems Biomedicine 2013; 1:35 - 34;
Ben-Hamo R, Efroni S.

Spatial Regulation Dominates Gene Function in the Ganglia Chain

Bioinformatics (2014) 30 (3): 310-316
Dror Hibsh, Hadas Schori, Sol Efroni, Orit Shefi

Classification of lung adenocarcinoma and squamous cell carcinoma samples based on their gene expression profile in the sbv IMPROVER Diagnostic Signature Challenge.

Systems Biomedicine 2013; 1:68 - 77;
Ben-Hamo R, Boue S, Martin F, Talikka M, Efroni S.

IL-27 acts on DCs to suppress the T cell response and autoimmunity by inducing expression of the immunoregulatory molecule CD39

Nature Immunology (14) 1054-1063
Ivan D Mascanfroni, Ada Yeste, Silvio M Vieira, Evan J Burns, Bonny Patel, Ido Sloma, Yan Wu, Lior Mayo, Rotem Ben-Hamo, Sol Efroni, Vijay K Kuchroo, Simon C Robson & Francisco J Quintana

Altered immune pathway activity under exercise challenge in Gulf War Illness: An exploratory analysis.

Brain Behav Immun. 2013 Feb;28:159-69.
Broderick G, Ben-Hamo R, Vashishtha S, Efroni S, Nathanson L, Barnes Z, Fletcher MA, Klimas N.

Systems analysis utilising pathway interactions identifies sonic hedgehog pathway as a primary biomarker and oncogenic target in hepatocellular carcinoma

IET Systems Biology, Volume 7, Issue 6, December 2013, p. 243 – 251
Efroni S, Meerzaman D, Schaefer CF, Greenblum S, Soo-Lyu M, Hu Y, Cultraro C, Meshorer E, Buetow KH.

hsa-miR-9 and drug control over the P38 network as driving disease outcome in GBM patients

Systems Biomedicine 2013; 1:76 - 83
Ben-Hamo R, Efroni S