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    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... 

    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... 

    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... 

    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... 

    Development and in vitro evaluation of photocurable GelMA/PEGDA hybrid hydrogel for corneal stromal cells delivery

    , Article Materials Today Communications ; Volume 27 , 2021 ; 23524928 (ISSN) Mahdavi, S. S ; Abdekhodaie, M. J ; Mashayekhan, S ; Baradaran Rafii, A ; Kim, K ; Sharif University of Technology
    Elsevier Ltd  2021
    Gelatin methacrylate (GelMA) was proved to be a promising bioink for corneal stromal cell delivery. However, GelMA has low mechanical properties which makes it difficult to be suturable and handled for clinical applicattion. In this study, three different ratios of 12.5 % GelMA and 10 % PEGDA were investigated for corneal stromal cells delivery. The mixture containing 75 % GelMA and 25 % PEGDA (75G25P) was found to have reasonable cell viability and suturing strength. Moreover, collagen nanofibers were incorporated into 75G25P hydrogel to improve the mechanical and biomimetic properties of the construct (75G25P-E). A hybrid structure was obtained by injecting the optimized bioink on the... 

    Utilization of gene expression programming for modeling of mechanical performance of titanium/carbonated hydroxyapatite nanobiocomposites: The combination of artificial intelligence and material science

    , Article International Journal of Engineering, Transactions A: Basics ; Volume 34, Issue 4 , 2021 , Pages 948-955 ; 17281431 (ISSN) Shojaei, M. R ; Khayati, G. R ; Hasani, A ; Sharif University of Technology
    Materials and Energy Research Center  2021
    Titanium carbonated hydroxyapatite (Ti/CHA) nanobiocomposites have extensive biological applications due to the excellent biocompatibility and similar characteristics to the human bone. Ti/CHA nanobiocomposite has good biological properties but it suffer from diverse characteristics especially in hardness, Young's modulus, apparent porosity and relative density. This investigation is an attempt to propose the predictive models using gene expression programming (GEP) to estimate these characteristics. In this regards, GEP is used to model and compare the effect of practical variables including pressure, Ti/CHA contents and sintering temperature on their monitored properties. To achieve this... 

    Using Transductive Learning Classification in Bioinformatics

    , M.Sc. Thesis Sharif University of Technology Tajari, Hossein (Author) ; Beigy, Hamid (Supervisor)
    Classification is one of the most important problems in machine learning area. Reliable and successful classification is essential for diagnosing patients for further treatment. In many applications such as bioinformatics unlabeled data is abundant and available. However labeling data is much more difficult and expensive to obtain. This dissertation presents a novel transductive approach for the development of robust microarray data classification. The transduction problem is to estimate the value of classification function at the given points in the working set. This contrasts with the standard inductive learning problem of estimating the classification method at all possible values and... 

    Identification of the Set of Single Nucleotide Variants in Genome Responsible for the Differentiation of Expression of Genes

    , M.Sc. Thesis Sharif University of Technology Khatami, Mahshid (Author) ; Rabiee, Hamid Reza (Supervisor) ; Beigi, Hamid (Supervisor)
    Single nucleotide polymorphs, There are changes caused by a mutation in a nucleotide in the Dena sequence. Mononucleotide polymorphisms are the most common type of genetic variation. Some of these changes have little or no effect on cells, while others cause significant changes in the expression of cell genes that can lead to disease or resistance to certain diseases. Because of the importance of these changes and their effect on cell function, the relationships between these changes are also important. Over the past decade, thousands of single disease-related mononucleotide polymorphisms have been identified in genome-related studies. Studies in this field have shown that the expression of... 

    Fuzzy support vector machine: An efficient rule-based classification technique for microarrays

    , Article BMC Bioinformatics ; Volume 14, Issue SUPPL13 , 2013 ; 14712105 (ISSN) Hajiloo, M ; Rabiee, H. R ; Anooshahpour, M ; Sharif University of Technology
    Background: The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification.Results: Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection... 

    Analysis of Gene Expression Data in Bioinformatics Data Sets Using Machine Learning Approaches

    , M.Sc. Thesis Sharif University of Technology Bagherian, Misagh (Author) ; Beigy, Hamid (Supervisor)
    As a robust and accurate classification of tumors is necessary for successful treatment of cancer, classification of DNA microarray data has been widely used in successful diagnosis of cancers and some other biological diseases. But the main challenge in classification of microarray data is the extreme asymmetry between the dimensionality of features (usually thousands or even tens of thousands of genes) and that of tissues (few hundreds of samples). Because of such curse of dimensionality, a class prediction model could be very successful in classifying one type of dataset but may fail to perform well in some other ones. Overfitting is another problem that prevents conventional learning... 

    A Semi-Supervised Algorithms for Clustering Microarray Data

    , M.Sc. Thesis Sharif University of Technology Eslamzadeh, Habibollah (Author) ; Mahdavi Amiri, Nezamoddin (Supervisor) ; Madadkar Sobhani, Armin (Supervisor)
    Microarray which is also known as Biochip is a flat substrate of glass with the size of 1 ×1 cm on which a numerous number of biosensors are placed in an array format. Microarray DNAs are used to measure expression level of thousands of genes. Repeating these experiments in different conditions can result in patterns of expression. After preparation, the florescent sample is hybridized with the sensors of microarray surface and fluoresce intensities of the spots are measured by a special camera called CCD. The obtained pictures are examined by a computer and the spot lights converted into numerical data by image processing algorithms. Putting these numbers into matrices of size m×n is... 

    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... 

    Distributed Processing of Next Generation Sequencing Data Set

    , M.Sc. Thesis Sharif University of Technology Hadadian Nejad Yousefi, Mostafa (Author) ; Goudarzi, Maziar (Supervisor) ; Motahari, Abolfazl (Supervisor)
    DNA analysis plays a significant role in fields such as pharmacy, agriculture, genealogy, and forensics. Next generation sequencing datasets cover a gene several times due to a large number of readings. Therefore, the initial data volume is several times the amount of memory required to store the DNA strand. First, the DNA sequence of a sample should be made using the primary data, and then the difference should be found by comparing the sample DNA sequence with the reference DNA sequence. By finding these differences, one can extract the characteristics of the tested species. The extracted properties are precious for genetics researchers. For example, they can produce drugs that are... 

    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... 

    Analysis of Genes Regulating Beta Cells Cell Cycle

    , M.Sc. Thesis Sharif University of Technology Saraei, Tannaz (Author) ; Motahari, Abolfazl (Supervisor)
    Diabetes mellitus is a group of disorders where the level of blood sugar remains high for a long period of time. This increase may be due to either reduced insulin secretion from the pancreatic gland, or insulin resistance, or both. Another key reason is the destruction of beta cells due to functional defect in the body’s immune system. Current treatments include controlling diet, insulin injection and pancreatic transplantation, all of which are temporary. For this reason, finding genetic factors participating in the progression of the disease and adapting treatments to these factors are under intensive studies.In this thesis, available information resources including genomic, biological... 

    Deep feature extraction of single-cell transcriptomes by generative adversarial network

    , Article Bioinformatics ; Volume 37, Issue 10 , 2021 , Pages 1345-1351 ; 13674803 (ISSN) Bahrami, M ; Maitra, M ; Nagy, C ; Turecki, G ; Rabiee, H. R ; Li, Y ; Sharif University of Technology
    Oxford University Press  2021
    Motivation: Single-cell RNA-sequencing (scRNA-seq) offers the opportunity to dissect heterogeneous cellular compositions and interrogate the cell-type-specific gene expression patterns across diverse conditions. However, batch effects such as laboratory conditions and individual-variability hinder their usage in cross-condition designs. Results: Here, we present a single-cell Generative Adversarial Network (scGAN) to simultaneously acquire patterns from raw data while minimizing the confounding effect driven by technical artifacts or other factors inherent to the data. Specifically, scGAN models the data likelihood of the raw scRNA-seq counts by projecting each cell onto a latent embedding.... 

    Nanofibrous hydrogel with stable electrical conductivity for biological applications

    , Article Polymer (United Kingdom) ; Volume 97 , 2016 , Pages 205-216 ; 00323861 (ISSN) Hosseinzadeh, S ; Rezayat, S. M ; Vashegani Farahani, E ; Mahmoudifard, M ; Zamanlui, S ; Soleimani, M ; Sharif University of Technology
    Elsevier Ltd 
    3D hydrogel environment with both unique properties of nanofibrous structure and electrical character can provide a promising scaffold for skeletal muscle tissue engineering approaches. Herein, the poly acrylic acid (PAA)-based hydrogel was engineered to conductive one by aniline polymerization in the form of nanofibers. The poly aniline (PANi) nanofibers were made by the optimized chemical reactions between the surface carboxylate groups of based hydrogel and protonated aniline monomers. We found that the strong bonding which was created between PANi and camphor sulphonic acid (CSA) as a doping agent supporting the stable electrical property of composite hydrogel after incubation in cell... 

    Apoptotic and anti-apoptotic genes transcripts patterns of graphene in mice

    , Article Materials Science and Engineering C ; Volume 71 , 2017 , Pages 460-464 ; 09284931 (ISSN) Ahmadian, H ; Hashemi, E ; Akhavan, O ; Shamsara, M ; Hashemi, M ; Farmany, A ; Daliri Joupari, M ; Sharif University of Technology
    Elsevier Ltd  2017
    Recent studies showed that a large amount of graphene oxide accumulated in kidney and liver when it injected intravenously. Evaluation of lethal and apoptosis gene expression in these tissues, which are under stress is very important. In this paper the in vivo dose-dependent effects of graphene oxide and reduced graphene oxide nanoplatelets on kidney and liver of mice were studied. Balb/C mice were treated by 20 mg/kg body weight of nanoplatelets. Molecular biology analysis showed that graphene nanoplatelets injected intravenously lead to overexpression of BAX gene in both kidney and liver tissues (P ≥ 0.01). In addition these nanoparticles significantly increase BCL2 gene expression in both... 

    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... 

    Rigorous silica solubility estimation in superheated steam: Smart modeling and comparative study

    , Article Environmental Progress and Sustainable Energy ; Volume 38, Issue 4 , 2019 ; 19447442 (ISSN) Rostami, A ; Shokrollahi, A ; Esmaeili Jaghdan, Z ; Ghazanfari, M. H ; Sharif University of Technology
    John Wiley and Sons Inc  2019
    One of the main issues of wastewater treatment is the silica deposition in steam turbines. Evaporation of silica with the steam in adequate concentration is one of the main sources of scale formation in steam turbines. In this study, the authors introduce the utilization of a genetic-based approach—gene expression programming (GEP)—for solubility prognostication of the silica in superheated steam of boilers with respect to water silica content and pressure. The result of GEP mathematical approach is a new algebraic formula to achieve our goals. Developed model predicts the silica solubility in the range of 0.8–22.1 MPa and 1–500 mg/kg for pressure and boiler water silica content,...