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    Neural network-based approaches, solving haplotype reconstruction in MEC and MEC/GI models

    , Article Neural Computing and Applications ; Volume 22, Issue 7-8 , 2013 , Pages 1397-1405 ; 09410643 (ISSN) Moeinzadeh, M. H ; Asgarian, E ; Sharifian-R. S ; Sharif University of Technology
    2013
    Abstract
    Single nucleotide polymorphism (SNP) in human genomes is considered to be highly associated with complex genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of recent studies on human genomics. The two sequences of SNPs in diploid human organisms are called haplotypes. In this paper, the problem of haplotype reconstruction from SNP fragments with and without genotype information is studied. Minimum error correction (MEC) is an important model for this problem but only effective when the error rate of the fragments is low. MEC/GI, as an extension to MEC model, employs the related genotype information besides the SNP fragments and,... 

    Comparative Analysis of Haplotype Assembly Algorithms to Identify and Propose Optimal Methods

    , M.Sc. Thesis Sharif University of Technology Bagher, Melina (Author) ; Jahed, Mehran (Supervisor) ; Hossein Khalaj, Babak (Supervisor)
    Abstract
    Humans, as a diploid species, have two nucleotide sequences of homologous chromosomes in their genomes, where one set is inherited from the mother, and the other comes from the father. The Single Individual Haplotype assembly problem (SIH) refers to the reconstruction of these two distinct nucleotide sequences of a chromosome from the sequencing reads, and it is currently considered one of the most important issues in the field of computational genomics, which plays an essential role in solving various genetic and medical problems.Nowadays direct experimental methods are not welcomed due to their high cost, and labor intensity, and are limited to certain regions of the genome, therefore,... 

    Three heuristic clustering methods for haplotype reconstruction problem with genotype information

    , Article Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, 18 November 2007 through 20 November 2007 ; 2007 , Pages 402-406 ; 9781424418411 (ISBN) Moeinzadeh, M. H ; Asgarian, E ; Najafi Ardabili, A ; Sharifian R, S ; Sheikhaei, M. S ; Mohammadzadeh, J ; Sharif University of Technology
    IEEE Computer Society  2007
    Abstract
    Most positions of the human genome are typically invariant (99%) and only some positions (1%) are commonly variant which are associated with complex genetic diseases. Haplotype reconstruction is to divide aligned SNP fragments, which is the most frequent form of difference to address genetic diseases, into two classes, and thus inferring a pair of haplotypes from them. Minimum error correction (MEC) is an important model for this problem but only effective when the error rate of the fragments is low. MEC/GI as an extension to MEC employs the related genotype information besides the SNP fragments and so results in a more accurate inference. The haplotyping problem, due to its NP-hardness, may... 

    Solving MEC and MEC/GI problem models, using information fusion and multiple classifiers

    , Article Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, 18 November 2007 through 20 November 2007 ; 2007 , Pages 397-401 ; 9781424418411 (ISBN) Asgarian, E ; Moeinzadeh, M. H ; Mohammadzadeht, J ; Ghazinezhad, A ; Habibi, J ; Najafi Ardabili, A ; Sharif University of Technology
    IEEE Computer Society  2007
    Abstract
    Mutations in Single Nucleotide Polymorphisms (SNPs - different variant positions (1%) from human genomes) are responsible for some genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of recent studies in human genomics. Two sequences of mentioned SNPs in diploid human organisms are called haplotypes. In this paper, we study haplotype reconstruction from SNP-fragments with and without genotype information, problems. Designing serial and parallel classifiers was center of our research. Genetic algorithm and K-means were two components of our approaches. This combination helps us to cover the single classifier's weaknesses. ©2008 IEEE  

    Colorimetric assay for exon 7 SMN1/SMN2 single nucleotide polymorphism using gold nanoprobes

    , Article BioImpacts ; Volume 3, Issue 4 , 2013 , Pages 185-194 ; 22285652 (ISSN) Ahmadpour Yazdi, H ; Hormozi Nezhad, M. R ; Abadi, A ; Sanati, M. H ; Kazemi, B ; Sharif University of Technology
    2013
    Abstract
    Introduction: Proximal spinal muscular atrophy (SMA) is one of the most significant neurodegenerative diseases amongst the autosomal-recessive genetic disorders which is caused by the absence of protein survival of motor neuron (SMN). A critical nucleotide difference in SMN2 compared to SMN1 gene leads to an inefficient protein. Hence, homozygous lack of SMN1 provides a progressive disease. Due to the high prevalence, up to now, several molecular diagnostic methods have been used which most of them are lengthy, expensive, and laborious. Methods: In the present study, we exploited a gold nanoprobe-based method for semi-quantitative SMN1 gene dosage analysis compared to SMN2. The assay was... 

    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
    Abstract
    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... 

    Conifer: clonal tree inference for tumor heterogeneity with single-cell and bulk sequencing data

    , Article BMC Bioinformatics ; Volume 22, Issue 1 , 2021 ; 14712105 (ISSN) Baghaarabani, L ; Goliaei, S ; Foroughmand Araabi, M. H ; Shariatpanahi, P ; Goliaei, B ; Sharif University of Technology
    BioMed Central Ltd  2021
    Abstract
    Background: Genetic heterogeneity of a cancer tumor that develops during clonal evolution is one of the reasons for cancer treatment failure, by increasing the chance of drug resistance. Clones are cell populations with different genotypes, resulting from differences in somatic mutations that occur and accumulate during cancer development. An appropriate approach for identifying clones is determining the variant allele frequency of mutations that occurred in the tumor. Although bulk sequencing data can be used to provide that information, the frequencies are not informative enough for identifying different clones with the same prevalence and their evolutionary relationships. On the other... 

    Channelopathy-related SCN10A gene variants predict cerebellar dysfunction in multiple sclerosis

    , Article Neurology ; Volume 86, Issue 5 , 2016 , Pages 410-417 ; 00283878 (ISSN) Roostaei, T ; Sadaghiani, S ; Park, M. T. M ; Mashhadi, R ; Nazeri, A ; Noshad, S ; Salehi, M. J ; Naghibzadeh, M ; Moghadasi, A. N ; Owji, M ; Doosti, R ; Hashemi Taheri, A. P ; Rad, A. S ; Azimi, A ; Chakravarty, M. M ; Voineskos, A. N ; Nazeri, A ; Sahraian, M. A ; Sharif University of Technology
    Lippincott Williams and Wilkins 
    Abstract
    Objective: To determine the motor-behavioral and neural correlates of putative functional common variants in the sodium-channel NaV1.8 encoding gene (SCN10A) in vivo in patients with multiple sclerosis (MS). Methods: We recruited 161 patients with relapsing-onset MS and 94 demographically comparable healthy participants. All patients with MS underwent structural MRI and clinical examinations (Expanded Disability Status Scale [EDSS] and Multiple Sclerosis Functional Composite [MSFC]). Whole-brain voxel-wise and cerebellar volumetry were performed to assess differences in regional brain volumes between genotype groups. Resting-state fMRI was acquired from 62 patients with MS to evaluate... 

    Application of single-nucleotide polymorphisms in the diagnosis of autism spectrum disorders: a preliminary study with artificial neural networks

    , Article Journal of Molecular Neuroscience ; Volume 68, Issue 4 , 2019 , Pages 515-521 ; 08958696 (ISSN) Ghafouri Fard, S ; Taheri, M ; Omrani, M. D ; Daaee, A ; Mohammad Rahimi, H ; Kazazi, H ; Sharif University of Technology
    Springer New York LLC  2019
    Abstract
    Autism spectrum disorder (ASD) includes different neurodevelopmental disorders characterized by deficits in social communication, and restricted, repetitive patterns of behavior, interests or activities. Based on the importance of early diagnosis for effective therapeutic intervention, several strategies have been employed for detection of the disorder. The artificial neural network (ANN) as a type of machine learning method is a common strategy. In the current study, we extracted genomic data for 487 ASD patients and 455 healthy individuals. All individuals were genotyped in certain single-nucleotide polymorphisms within retinoic acid-related orphan receptor alpha (RORA), gamma-aminobutyric... 

    Human papilloma virus and breast cancer: The role of inflammation and viral expressed proteins

    , Article BMC Cancer ; Volume 19, Issue 1 , 2019 ; 14712407 (ISSN) Khodabandehlou, N ; Mostafaei, S ; Etemadi, A ; Ghasemi, A ; Payandeh, M ; Hadifar, S ; Norooznezhad, A. H ; Kazemnejad, A ; Moghoofei, M ; Sharif University of Technology
    BioMed Central Ltd  2019
    Abstract
    Background: Breast cancer is currently the most common neoplasm diagnosed in women globally. There is a growing body of evidence to suggest that human papillomavirus (HPV) infection may play a key role in invasiveness of breast cancer. The aim of this study was to determine the presence of HPV in patients with breast cancer and its possible association with cancer progression. Methods: Breast specimens were collected from 72 patients with breast cancer and 31 healthy controls. The presence of HPV was investigated by polymerase chain reaction (PCR) and genotyping was performed for positive cases. We also evaluated the viral factors such as E6, E2, and E7 in HPV positive cases. Enzyme-linked...