The European Human Genetics Conference 2022
PhD Student of our Lab Ohad Landau participated in The European Human Genetics Conference 2022 on JUNE 11–14, 2022 in Vienna, Austria organized by the European Society of Human Genetics.
A Collaborated Project published
The Rubin Lab’s collaborative effort with the Win Consortium was published in Wiley’s Cancer Medicine. Shai Magidi and Prof. Eitan Rubin (PI) work on the project with Win Consortium. The Simplified Interventional Mapping System (SIMS) was created by them to better describe the cancer molecular milieu using genomics/transcriptomics from tumor and similar normal tissue samples. To read the paper click here
Exposure to Research – Faculty of Health Sciences, BGU – 2022
The exposure to the research program has happened on the 22nd of March 2022. Our PI prof Eitan Rubin and The PhD Student of the Lab participated in the event
Rambam Hack
Lab members participated in a one day workshop on Machine Learning in Health Care, Organized by IDSI, and Technion together, in Rambam Hospital Haifa on 09th of March 2022
Chairing the Meeting
Principal Investigator, Prof. Eitan Rubin chairing a session on Computational Methods in Immune and Cancer Research of the 2nd Immuno-oncological Meeting of the Israel Immunological Society (IIS). The conference is
IDSI -2022 Conference
Kartheeswaran, A PhD student from the Lab participated in the IDSI -2022 conference held on 3-6 January 2022 at Ein Gedi
Yan Lender Successfully defended his MSc examination
MSc student of our lab Yan Lender successfully defended his MSc thesis examination on 23rd of December 2021 in ICI effect on EGFR LUAD
June 16, 2017 Lazar et. al “Use of dual biopsies and differential gene expression in tumor and normal matched tissues addresses the challenges of precision oncology and reveals new insights in the biology of Non- Small Cell Lung Carcinomas (NSCLC)” (under review)
This is temporary site, built for the sole purpose of hold supplementary information described in the paper. Supplemntary File 1
Improving Recurrence Prediction in Breast Cancer by Coupling Deep Learning and Random Forest
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