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    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... 

    Application of artificial neural network for prediction of risk of multiple sclerosis based on single nucleotide polymorphism genotypes

    , Article Journal of Molecular Neuroscience ; Volume 70, Issue 7 , 2020 , Pages 1081-1087 Ghafouri-Fard, S ; Taheri, M ; Omrani, M. D ; Daaee, A ; Mohammad Rahimi, H ; Sharif University of Technology
    Humana Press Inc  2020
    The artificial neural network (ANN) is a sort of machine learning method which has been used in determination of risk of human disorders. In the current investigation, we have created an ANN and trained it based on the genetic data of 401 multiple sclerosis (MS) patients and 390 healthy subjects. Single nucleotide polymorphisms (SNPs) within ANRIL (rs1333045, rs1333048, rs4977574 and rs10757278), EVI5 (rs6680578, rs10735781 and rs11810217), ACE (rs4359 and rs1799752), MALAT1 (rs619586 and rs3200401), GAS5 (rs2067079 and rs6790), H19 (rs2839698 and rs217727), NINJ2 (rs11833579 and rs3809263), GRM7 (rs6782011 and rs779867), VLA4 (rs1143676), CBLB (rs12487066) and VEGFA (rs3025039 and... 

    Inference of gene regulatory networks by extended Kalman filtering using gene expression time seriesdata

    , Article BIOINFORMATICS 2012 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms ; 2012 , Pages 150-155 ; 9789898425904 (ISBN) Fouladi, R ; Fatemizadeh, E ; Arab, S. S ; Sharif University of Technology
    In this paper, the Extended Kalman filtering (EKF) approach has been used to infer gene regulatory networks using time-series gene expression data. Gene expression values are considered stochastic processes and the gene regulatory network, a dynamical nonlinear stochastic model. Using these values and a modified Kalman filtering approach, the model's parameters and consequently the interactions amongst genes are predicted. In this paper, each gene-gene interaction is modeled using a linear term, a nonlinear one, and a constant term. The linear and nonlinear term coefficients are included in the state vector together with the gene expressions' true values. Through the extended Kalman... 

    Evaluation of the ankylosing spondylitis transcriptome for oxidative phosphorylation pathway: the shared pathway with neurodegenerative diseases

    , Article Iranian journal of allergy, asthma, and immunology ; Volume 20, Issue 5 , 2021 , Pages 563-573 ; 17355249 (ISSN) Lari, A ; Gholami Pourbadie, H ; Sharifi Zarchi, A ; Aslani, S ; Nejatbakhsh Samimi, L ; Jamshidi, A ; Mahmoudi, M ; Sharif University of Technology
    NLM (Medline)  2021
    Ankylosing spondylitis (AS) is a systemic inflammatory disorder of joints and entheses. Recent studies have reported an increased prevalence of dementia in AS patients. However, data for exploring the association between dementia and AS remain uncertain. In this study, enriched pathways and differentially expressed genes (DEGs) were identified in whole blood transcription data of AS patients obtained from the gene expression omnibus (GEO) database; using gene set enrichment analysis (GSEA) and differential expression analysis. Four pathways, including oxidative phosphorylation, Alzheimer's, Parkinson's, and Huntington's diseases were significantly enriched in AS patients compared to the... 

    Synthesis and Characterization of Zeolitic Imidazolate Framework-8 as a Carrier for Gene Therapy Applications

    , M.Sc. Thesis Sharif University of Technology Montazeri, Farzad (Author) ; Simchi, Abdolreza (Supervisor) ; Behmanesh, Mehrdad (Co-Supervisor)
    Advances in genetics and biology have led to the ability to produce therapeutic genes and modify defective genes in patients' genomes, resulting in a solution to many genetic diseases. Many genetic diseases can be overcome through gene therapy by transferring therapeutic genes into the cell nucleus. However, researchers have not yet been able to develop a safe, high-efficiency carrier for the transfer of genes to the target cell, and this has become a bottleneck for the clinical applications of gene therapy. In this study, the ZIF-8 organic-metallic framework was used as a new vector for the transfer of therapeutic genes to target cells. For this purpose, ZIF-8 was synthesized by a... 

    Smart micro/nano-robotic systems for gene delivery

    , Article Current Gene Therapy ; Volume 17, Issue 2 , 2017 , Pages 73-79 ; 15665232 (ISSN) Pedram, A ; Nejat Pishkenari, H ; Sharif University of Technology
    Bentham Science Publishers B.V  2017
    Background: Small scale robotics have attracted growing attention for the prospect of targeting and accessing cell-sized sites, necessary for high precision biomedical applications and drug/gene delivery. The loss of controlled gene therapy, inducing systemic side effects and reduced therapeutic efficiency, can be settled utilizing these intelligent carriers. Methods: Newly proposed solutions for the main challenges of control, power supplying, gene release and final carrier extraction/degradation have shifted these smart miniature robots to the point of being employed for practical applications of transferring oligonucleotides (pDNA, siRNA, mRNA, etc.) in near future. Conclusion: In this... 

    Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data

    , Article PloS one ; Volume 12, Issue 2 , 2017 , Pages e0171240- ; 19326203 (ISSN) Narimani, Z ; Beigy, H ; Ahmad, A ; Masoudi Nejad, A ; Fröhlich, H ; Sharif University of Technology
    Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary... 

    Identifying Core Genes in Estimation of Missing Gene Expressions

    , M.Sc. Thesis Sharif University of Technology Darvish Shafighi, Shadi (Author) ; Motahari, Abolfazl (Supervisor)
    Characterizing cellular states in response to various disease conditions is an important issue which is addressed by different methods such as Large-scale gene expression profiling. One of the most important challenges in front of bioinformaticians is the loss of data because expression profiling is still very expensive. It is understood that profiling a group of selected genes could be enough for understanding all of the gene expression profile.In this research, we propose a fast method for estimation of the missing values inlow-rank matrices. We consider the highly correlated expression profiles as a low-rank matrix. Then, we used this new method in a proposed algorithm which will select... 

    PFP-WGAN: Protein function prediction by discovering gene ontology term correlations with generative adversarial networks

    , Article PLoS ONE ; Volume 16, Issue 2 , 2021 ; 19326203 (ISSN) Seyyedsalehi, S. F ; Soleymani, M ; Rabiee, H. R ; Kaazempur Mofrad, M. R ; Sharif University of Technology
    Public Library of Science  2021
    Understanding the functionality of proteins has emerged as a critical problem in recent years due to significant roles of these macro-molecules in biological mechanisms. However, in-laboratory techniques for protein function prediction are not as efficient as methods developed and processed for protein sequencing. While more than 70 million protein sequences are available today, only the functionality of around one percent of them are known. These facts have encouraged researchers to develop computational methods to infer protein functionalities from their sequences. Gene Ontology is the most well-known database for protein functions which has a hierarchical structure, where deeper terms are... 

    Photoluminescent carbon quantum dot/poly-L-Lysine core-shell nanoparticles: A novel candidate for gene delivery

    , Article Journal of Drug Delivery Science and Technology ; 2020 Hasanzadeh, A ; Mofazzal Jahromi, M. A ; Abdoli, A ; Mohammad Beigi, H ; Fatahi, Y ; Nourizadeh, H ; Zare, H ; Kiani, J ; Radmanesh, F ; Rabiee, N ; Jahani, M ; Mombeiny, R ; Karimi, M ; Sharif University of Technology
    Editions de Sante  2020
    Cationic polymers such as poly-L-lysine (PLL) are able to interact electrostatically with DNA to produce polymeric systems with nanometric diameters due to the neutralization and accumulation of DNA. This study integrates the outstanding properties of carbon quantum dots (CQDs) with PLL to develop a novel gene delivery vehicle with a core-shell hybrid nanostructure. The CQD/PLL core-shell nanoparticles (NPs) were, therefore, synthesized in such a way that they had narrow size distribution and an average diameter under 10 nm, both of which were confirmed by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Fourier transform infrared (FTIR) spectroscopy exhibited that... 

    Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis

    , Article BMC Medical Genomics ; Volume 12, Issue 1 , 2019 ; 17558794 (ISSN) Karimizadeh, E ; Sharifi Zarchi, A ; Nikaein, H ; Salehi, S ; Salamatian, B ; Elmi, N ; Gharibdoost, F ; Mahmoudi, M ; Sharif University of Technology
    BioMed Central Ltd  2019
    Background: Systemic sclerosis (SSc), a multi-organ disorder, is characterized by vascular abnormalities, dysregulation of the immune system, and fibrosis. The mechanisms underlying tissue pathology in SSc have not been entirely understood. This study intended to investigate the common and tissue-specific pathways involved in different tissues of SSc patients. Methods: An integrative gene expression analysis of ten independent microarray datasets of three tissues was conducted to identify differentially expressed genes (DEGs). DEGs were mapped to the search tool for retrieval of interacting genes (STRING) to acquire protein-protein interaction (PPI) networks. Then, functional clusters in PPI... 

    Role of endurance training in preventing pathological hypertrophy via large tumor suppressor (LATS) changes

    , Article Iranian Heart Journal ; Volume 20, Issue 3 , 2019 , Pages 52-59 ; 17357306 (ISSN) Tabrizi, A ; Soori, R ; Choobineh, S ; Gholipour, M ; Sharif University of Technology
    Iranian Heart Association  2019
    Background: One of the negative effects of cardiac sympathetic hyperactivity is pathologic hypertrophy. Recent studies have indicated that large tumor suppressor (LATS) is one of the molecules which play a critical role in cardiomyocyte apoptosis. Considering the preventive role of exercise training, we evaluated the effects of endurance training on LATS gene expression and its upstream pathway in the present study. Methods: Eighteen male Wistar rats were randomly divided into 2 groups: Endurance and control. Endurance training was performed for 8 weeks, 1 hour per day, and 6 days per week on the treadmill at a 15° inclination. Pathologic hypertrophy was induced with the injection of 3... 

    Inferring Gene Regulatory Networks, Using Machine Learning Approaches

    , M.Sc. Thesis Sharif University of Technology Gheiby, Sanaz (Author) ; Manzuri, Mohammad Taghi (Supervisor)
    Gene regulatory network consists of a set of genes; interacting with each other via their protein products. Such interations lead to the regulation of the genes’ production rate. A breakdown in the regulatory process, may lead to some kinds of diseases. Therefore, understanding the gene regulatory process, is beneficial for both diagnosis and treatment. In this thesis, gene regulatory networks are modeled by the means of dynamic Bayesian networks. We have used sampling based methods, in order to learn the network structure. As these methos have a very high computational cost; we have used a correlation test to prune the search space. This way, an undirected network skeleton is obtained; for... 

    Bayesian Filtering Approach to Improve Gene Regulatory Networks Inference Using Gene Expression Time Series

    , M.Sc. Thesis Sharif University of Technology Fouladi, Ramouna (Author) ; Fatemizadeh, Emadoddin (Supervisor) ; Arab, Shahriar (Co-Advisor)
    Gene regulatory modeling in different species is one of the main aims of Bioinformatics. Regarding the limitations of the data available and the perspectives which should be taken into account for modeling such networks, proposed methods up to now have not yet been successful in yielding a comprehensive model. In one of the recent researches, the Gene regulation process is considered as a nonlinear dynamic stochastic process and described by state space equations. Afterwards, in order for the unknown parameters to be estimated, Extended Kalman Filtering is used. In this thesis, first of all, Gene complexes are taken into consideration instead of genes and afterwards, Extended Kalman... 

    Detection and Estimation of Key Parameters in Traffic Models Using Data Mining Tools

    , M.Sc. Thesis Sharif University of Technology Moadab, Amir Hossein (Author) ; Khedmati, Majid (Supervisor)
    Nowadays, investigating the factors affecting traffic models from different aspects such as metropolitan planning according to the present conditions can help high-level decision-makers and also, at the micro-level, help the travelers to make appropriate decisions for scheduling affairs, route selection, and vehicle type selection. Given the importance of this topic, a framework will be presented in this study that will evaluate the impact of some identified factors such as travel distance, climate, and urban events, and then all these factors will be presented in mathematical formulas. In the end, based on the model, the travel time will be predicted. In this framework, gene expression... 

    Toward chemical perfection of graphene-based gene carrier via ugi multicomponent assembly process

    , Article Biomacromolecules ; Volume 17, Issue 9 , 2016 , Pages 2963-2971 ; 15257797 (ISSN) Rezaei, A ; Akhavan, O ; Hashemi, E ; Shamsara, M ; Sharif University of Technology
    American Chemical Society 
    The graphene-based materials with unique, versatile, and tunable properties have brought new opportunities for the leading edge of advanced nanobiotechnology. In this regard, the use of graphene in gene delivery applications is still at early stages. In this study, we successfully designed a new complex of carboxylated-graphene (G-COOH) with ethidium bromide (EtBr) and used it as a nanovector for efficient gene delivery into the AGS cells. G-COOH, with carboxyl functions on its surface, in the presence of EtBr, formaldehyde, and cyclohexylisocyanide were participated in Ugi four component reaction to fabricate a stable amphiphilic graphene-EtBr (AG-EtBr) composite. The coupling reaction was... 

    Temperature-responsive smart nanocarriers for delivery of therapeutic agents: applications and recent advances

    , Article ACS Applied Materials and Interfaces ; Volume 8, Issue 33 , 2016 , Pages 21107-21133 ; 19448244 (ISSN) Karimi, M ; Sahandi Zangabad, P ; Ghasemi, A ; Amiri, M ; Bahrami, M ; Malekzad, H ; Ghahramanzadeh Asl, H ; Mahdieh, Z ; Bozorgomid, M ; Ghasemi, A ; Rahmani Taji Boyuk, M. R ; Hamblin, M. R ; Sharif University of Technology
    American Chemical Society  2016
    Smart drug delivery systems (DDSs) have attracted the attention of many scientists, as carriers that can be stimulated by changes in environmental parameters such as temperature, pH, light, electromagnetic fields, mechanical forces, etc. These smart nanocarriers can release their cargo on demand when their target is reached and the stimulus is applied. Using the techniques of nanotechnology, these nanocarriers can be tailored to be target-specific, and exhibit delayed or controlled release of drugs. Temperature-responsive nanocarriers are one of most important groups of smart nanoparticles (NPs) that have been investigated during the past decades. Temperature can either act as an external... 

    CytoGTA: a cytoscape plugin for identifying discriminative subnetwork markers using a game theoretic approach

    , Article PLoS ONE ; Volume 12, Issue 10 , 2017 ; 19326203 (ISSN) Farahmand, S ; Foroughmand Araabi, M. H ; Goliaei, S ; Razaghi Moghadam, Z ; Sharif University of Technology
    In recent years, analyzing genome-wide expression profiles to find genetic markers has received much attention as a challenging field of research aiming at unveiling biological mechanisms behind complex disorders. The identification of reliable and reproducible markers has lately been achieved by integrating genome-scale functional relationships and transcriptome datasets, and a number of algorithms have been developed to support this strategy. In this paper, we present a promising and easily applicable tool to accomplish this goal, namely CytoGTA, which is a Cytoscape plug-in that relies on an optimistic game theoretic approach (GTA) for identifying subnetwork markers. Given transcriptomic... 

    Carbosilane dendrimers: Drug and gene delivery applications

    , Article Journal of Drug Delivery Science and Technology ; Volume 59 , 2020 Rabiee, N ; Ahmadvand, S ; Ahmadi, S ; Fatahi, Y ; Dinarvand, R ; Bagherzadeh, M ; Rabiee, M ; Tahriri, M ; Tayebi, L ; Hamblin, M. R ; Sharif University of Technology
    Editions de Sante  2020
    Carbosilane dendrimers are a particular type of dendrimer structure that has been used as delivery vehicles for drugs and nucleic acids. They have a defined structure according to their generation number, and their terminal groups can be rendered cationic or anionic. The cationic charges can address the limitation of electrostatic repulsion between the negatively charged phosphate groups of nucleic acids and negatively charged cell membranes. Specific drugs can be loaded into the central part of the dendrimer or attached at the exterior, and the overall positive charge may improve the efficacy of anti-inflammatory drugs. One promising feature of dendrimers is their non-toxicity both in vitro... 

    Graph Reductions and its Application in Parallel Gene Assembly

    , M.Sc. Thesis Sharif University of Technology Azadi, Mohammad (Author) ; Mahmoodian, Ebadollah (Supervisor)
    In the process of gene assembling, the molecular structure of a DNA chain, can be modeled by a signed graph. After that by means of a composition of three reduction rules: gnr, gpr and gdr, that is called reduction strategy, this graph is reduced to a null graph. If the composition of any ordering of rules in a reduction strategy such as S, is applicable on a signed graph G, then we say that S can be applied in parallel to G and the set S is said to be a parallel step for reduction of that graph. Also we define the least number of parallel steps in reduction of a graph, to be the parallel complexity of that graph, and denote it C(G). In this thesis, a collection of particular signed graphs,...