PhD and MSc Theses
PhD and MSc Theses, since 1988
Student’s Name |
Graduation Year |
Degree |
Abstracts |
Research Name |
Baruchi Farber Hodaya |
2024 |
PhD |
Abstracts |
Identifying Metabolic Alterations and Vulnerabilities in Therapy-Induced Senescent Cells |
Sarvin Boris |
2021 |
PhD |
Abstracts |
Mass Spectrometry Approaches for Studying Cancer Metabolism |
Mukha Dzmitry |
2021 |
PhD |
|
Hepatocellular Carcinoma Depends on Glycine Decarboxylase to Maintain Mitochondrial Activity and Growth |
Lee Won Dong |
2019 |
PhD |
Abstracts |
Characterization of Cancer Metabolism at the Subcellular Level: an Integrated Experimental-Computational Approach |
Fokra Miriam |
2023 |
PhD |
Abstracts |
Targeting One-Carbon Metabolism in Hepatocellular Carcinoma |
Stern Alon |
2022 |
PhD |
Abstracts |
Methods for Inferring Compartmentalized Fluxes and Concentrations in Mammalian Cells |
Lagziel Shoval |
2021 |
PhD |
|
Computational Inference of Cancer Metabolic Alterations for Early Diagnosis and Treatment |
Ahn Eunyong |
2018 |
PhD |
Abstracts |
Characterization of Cellular Metabolism throughout the Cell Cycle in Cancer: An Integrated Experimental- Computational Approach |
Tepper Naama |
2016 |
PhD |
Abstracts |
Computational Methods for Metabolic Network Analysis of Metabolite Levels and Flux |
Fridman Eran |
2022 |
PhD |
Abstracts |
Macrophage Derived Exosomes Modulate Pancreatic Cancer Metabolism |
Rutenberg Abraham |
2022 |
PhD |
|
Overcoming Metabolic T Cell Suppression in Cancer Immunotherapy using Nanotechnology-based Metabolite Feeding |
Baruchi Farber Hodaya |
2019 |
MSc |
Abstracts |
Identifing Metabolic Alterations and Vulnerabilites in Senescent Cancer Cells |
Balber Michael |
2017 |
MSc |
|
Constraint-Based Isotope Tracing (CBIT): Inferring Flux Constraints from Isotopic Tracing Data |
Adadi Roi |
2011 |
MSc |
Abstracts |
Prediction of Microbial Growth Rate versus Biomass Yield by a Metabolic Network with Kinetic Parameters |
Vitkin Edward |
2011 |
MSc |
Abstracts |
Functional Genomics Based Approach for Reconstruction of Genome Scale Metabolic Network Models |