Search for: receptor--epidermal-growth-factor
Article PLoS ONE ; Volume 12, Issue 8 , 2017 ; 19326203 (ISSN) ; Habibi, J ; Sharif University of Technology
Public Library of Science 2017
Background: Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods: In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for...
Article OncoTargets and Therapy ; Volume 14 , 2021 , Pages 4309-4318 ; 11786930 (ISSN) ; Al Saraireh, Y. M ; Youssef, A. M. M ; Al Sarayra, Y. M ; Alrawashdeh, H. M ; Sharif University of Technology
Dove Medical Press Ltd 2021
Purpose: Treatment of metastatic breast cancer patients is challenging and remains a major underlying cause of female mortality. Understanding molecular alterations in tumor development is critical to identify novel biomarkers and targets for cancer diagnosis and therapy. One of the aberrant cancer expressions gaining recent research interest is glypican-1. Several studies reported strong glypican-1 expression in various types of human cancers. However, none of these investigated glypican-1 expression in a large cohort of breast cancer histopathological subtypes. Patients and Methods: Immunohistochemistry was used to assess glypican-1 expression in 220 breast cancer patients and its relation...
Article PLoS ONE ; Volume 7, Issue 6 , 2012 ; 19326203 (ISSN) ; Masoudi Nejad, A ; Jalili, M ; Moeini, A ; Sharif University of Technology
Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational...