About Me

I was born in Zarrin Shahr, Isfahan, Iran. I got my BA in Solid State Physics (2012-16) and my MSc (2016-18) in Physics of Complex Systems from Shahid Beheshti University (SBU) in Tehran. For my MSc project, I worked on cancer with a maximum entropy approach at the Center For Complex Networks & Social Data Science (CCNSD) of SBU. The idea behind my project was to apply a spin-glass model to a Gene Regulatory Network (GRN) to infer/learn the weight of the GRN’s links and then, given the network, compare the GRN of the normal and cancerous cell.

I am generally interested in: Complex Systems, Network Science, and Data Science.

About My Master’s Thesis

Almost all the studies about cancers are based on finding effective genes for each cancer and neglecting the collective behavior of the genes emerged from the regulatory effects of them on each other in a cell. In our study, we have considered each gene as a spin in a spin-glass (multivariate Gaussian) model and the gene-gene interaction as the coupling between each pair of the spins. By applying the principle of max. entropy, we have inferred the network of interactions from RNA-Seq data of genes expression levels in the case of Breast Cancer. This network is a signed weighted network, so according to the framework of Balance Theory, we could assign energy to the triads and the entire network.

Our results show that (i) for each type of triads in the network, whether frustrated or relaxed, their energy distributions are of a power-law form. Besides, (ii) the energy pattern in the normal case is more localized and more assortative. (iii) The energy level of the normal network is higher than the cancerous one, meaning the normal cell has more tendency toward frustration. From a dynamical point of view, it seems that there are some collective modes in the cancerous cell which we are interested to study in the future.