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    Inferring signaling pathways using interventional data

    , Article Intelligent Data Analysis ; Volume 17, Issue 2 , April , 2013 , Pages 295-308 ; 1088467X (ISSN) Mazloomian, A ; Beigy, H ; Sharif University of Technology
    Studying biological networks helps to gain a better understanding of cellular behaviors. One of the prominent models to study complex interactions in biological networks is the Nested Effects Model (NEM). Based on the Nested Effects Model, we propose two methods for inferring signaling pathways from interventional data. In the first method, we search the space of all feasible solutions with an evolutionary approach to maximize a standard Bayesian score. In the second method, sub-models are constructed with informative features and then combined using an averaging method to make the analysis of larger networks computationally possible. We tested our proposed methods in various noise levels on... 

    Inferring Signaling Pathways from RNAi Data Using Machine Learning

    , M.Sc. Thesis Sharif University of Technology Mazloomian, Alborz (Author) ; Beigy, Hamid (Supervisor)
    One of the standing problems in Molecular Biology and Bioinformatics is uncovering signaling pathways. Discovering the causes of many cancer-like diseases and developing better treatments for them, requires a better understanding of the behavior of cellular processes. Understanding signaling pathways can help to realize cellular processes. Due to the fast increase of possible signaling pathways when the number of components increases, the problem seems to have an inherent complexity. One of the recent methods for generating data relating to such networks is RNA interference technique. In this thesis we use data which are provided by this method. We propose two methods to infer signaling... 

    Temporal activation of LRH-1 and RAR-γ in human pluripotent stem cells induces a functional naïve-like state

    , Article EMBO Reports ; Volume 21, Issue 10 , 2020 Taei, A ; Kiani, T ; Taghizadeh, Z ; Moradi, S ; Samadian, A ; Mollamohammadi, S ; Sharifi Zarchi, A ; Guenther, S ; Akhlaghpour, A ; Asgari Abibeiglou, B ; Najar Asl, M ; Karamzadeh, R ; Khalooghi, K ; Braun, T ; Hassani, S. N ; Baharvand, H ; Sharif University of Technology
    Wiley-VCH Verlag  2020
    Naïve pluripotency can be established in human pluripotent stem cells (hPSCs) by manipulation of transcription factors, signaling pathways, or a combination thereof. However, differences exist in the molecular and functional properties of naïve hPSCs generated by different protocols, which include varying similarities with pre-implantation human embryos, differentiation potential, and maintenance of genomic integrity. We show here that short treatment with two chemical agonists (2a) of nuclear receptors, liver receptor homologue-1 (LRH-1) and retinoic acid receptor gamma (RAR-γ), along with 2i/LIF (2a2iL) induces naïve-like pluripotency in human cells during reprogramming of fibroblasts,... 

    Discovering dominant pathways and signal-response relationships in signaling networks through nonparametric approaches

    , Article Genomics ; Volume 102, Issue 4 , October , 2013 , Pages 195-201 ; 08887543 (ISSN) Nassiri, I ; Masoudi Nejad, A ; Jalili, M ; Moeini, A ; Sharif University of Technology
    A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises... 

    Genome-wide DNA methylation profiling in ectopic and eutopic of endometrial tissues

    , Article Journal of Assisted Reproduction and Genetics ; Volume 36, Issue 8 , 2019 , Pages 1743-1752 ; 10580468 (ISSN) Barjaste, N ; Shahhoseini, M ; Afsharian, P ; Sharifi Zarchi, A ; Masoudi Nejad, A ; Sharif University of Technology
    Springer New York LLC  2019
    Purpose: Endometriosis is a gynecological disease that causes the uterine lining to appear in other organs outside the uterus. As DNA methylation has an important role in this disorder, its profiling can reveal new information to improve the diagnosis and treatment of endometriosis patients. Methods: We conducted a genome-wide methylation profiling of ectopic and eutopic endometrial tissues from women with and without endometriosis using Infinium Human Methylation 450K BeadChip arrays. DNA methylation samples were collected from nine ectopic and nine eutopic endometrial tissues of endometriosis and six endometrial tissues of healthy controls. Results: Correlation heatmaps and the principal... 

    An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

    , Article Arthritis Research and Therapy ; Volume 22, Issue 1 , June , 2020 Maleknia, S ; Salehi, Z ; Rezaei Tabar, V ; Sharifi Zarchi, A ; Kavousi, K ; Sharif University of Technology
    BioMed Central  2020
    Background: A comprehensive intuition of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, is a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discover the unknown aspects. This study aimed to underscore key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention. Methods: In the present study, the human peripheral blood mononuclear cell (PBMC) microarray datasets (n = 6), generated by three platforms, which included SLE patients (n = 220) and healthy control samples (n = 135) were collected. Across each platform, we integrated the datasets by...