New methodology for repetitive sequences identification in human X and Y chromosomes

Touati, Rabeb; Tajouri, Asma; Mesaoudi, Imen; Oueslati, Afef Elloumi; Lachiri, Zied; Kharrat, Maher

doi:10.1016/j.bspc.2020.102207

Cited by 7 publications

(11 citation statements)

References 47 publications

(52 reference statements)

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“…After transforming the amino-acid sequence into a signal, we aimed to see it in a 2-D representation to focus more on the information that can contain. The Continuous Wavelet Transform (CWT) (along 64 scales with w 0 ~ 5.5) was applied to protein signal to obtain a protein image (2-D scalogram) [ 27 , 28 ]. corresponds to the oscillations number of wavelet transform, and the parameter f 0 is the central frequency of the basic wavelet.…”

Section: Methodsmentioning

confidence: 99%

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Intelligent system based comparative analysis study of SARS-CoV-2 spike protein and antigenic proteins in different types of vaccines

Touati

Elngar

2022

Beni-Suef Univ J Basic Appl Sci

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Background Coronaviruses, members of the Coronavirinae subfamily in the Coronaviridae family, are enveloped and positive-stranded RNA viruses that infect animals and humans, causing intestinal and respiratory infections. Coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus, named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This disease appeared, for the first time (December 2019), in China and has spread quickly worldwide causing a large number of deaths. Considering the global threat, the World Health Organization (WHO) has declared, in March 2020, COVID-19 as a pandemic. Many studies suggest the great effect of the existing vaccines to protect against symptomatic cases of death by the COVID-19 virus. This paper, proposes to compare the main antigenic proteins sequences of the existing vaccines with Spike (S) protein of the SARS-CoV-2 genome. Our choice of S protein is justified by the major role that plays it in the receptor recognition and membrane fusion process based on an intelligent system. Herein, we focus on finding a correlation between S protein and compulsory vaccines in the countries that have a less death number by COVID-19 virus. In this work, we have used a combination of coding methods, signal processing, and bioinformatic techniques with the goal to localize the similar patterns between the S gene of the SARS-Cov-2 genome and 14 investigated vaccines. Results A total of 8 similar sequences which have a size more than 6 amino acids were identified. Further, these comparisons propose that these segments can be implicated in the immune response against COVID-19, which may explain the wide variation by country in the severity of this viral threat. Conclusions Our in silico study suggests a possible protective effect of Poliovirus, HIB, Hepatitis B, PCV10, Measles, Mumps, and Rubella (MMR) vaccines against COVID-19.

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Section: Methodsmentioning

confidence: 99%

“… corresponds to the oscillations number of wavelet transform, and the parameter f 0 is the central frequency of the basic wavelet. These images (wavelet scalograms) are the best method to detect the homologous regions between two amino-acid sequences [ 27 , 28 ].…”

Section: Methodsmentioning

confidence: 99%

Intelligent system based comparative analysis study of SARS-CoV-2 spike protein and antigenic proteins in different types of vaccines

Touati

Elngar

2022

Beni-Suef Univ J Basic Appl Sci

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“…Graphical signature representation is a very important step to know the variation between different genomic sequences [31,[34][35][36][37][38][39][40]. The major advantage of this step is being unworthy of any need for any previously biological knowledge.…”

Section: Methodsmentioning

confidence: 99%

“…Obtain numerical DNA representations using different methods were used as an important step that specializes in DNA sequences if it contains repetition patterns [34][35][36][37][38][39][40] the EIIP mapping [41], the structural bending trinucleotide (PNUC) [42], the Frequency Chaos Game Signal (FCGS) [34][35][36][37][38][39][40], and so on.…”

Section: Genomic Image Representationsmentioning

confidence: 99%

“…The CGR image represents one DNA sequence unambiguously along with other sequences that reveal both local and global patterns hidden in it [31,[34][35][36][37][38][39][40][41][42][43][44][45]. This simple representation of DNA sequence is derived from chaos theory which was proposed, in 1990, by Jeffrey and it was considered as a mapping method of genome sequences [34,[43][44][45].…”

Section: Cgr Representationmentioning

confidence: 99%

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Different genomic representations of novel pathogens base on signal processing algorithms: COVID-19 case study

Touati

Touati²,

Benzarti³

et al. 2022

Preprint

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Coronaviruses are a type of frequent RNA virus. They are responsible for digestive and respiratory infections in animal and human genomes. A coronavirus renamed COVID-19 appeared and spread in the world which makes it declared in March 2020 a pandemic by the World Health Organization. SARS-CoV-2 genome, responsible for COVID-19 virus, has a size equal to 29,903 nucleotides, and its genetic makeup is composed of 11 functional open reading frames (ORFs). This paper proposes comparison algorithms to find SARS-Cov2 origin using digital genomic signatures. As a result, the five closest genomes related to SARS-CoV-2 are RaTG13, Pangolin-cov-PCoV_GX-P2V, Pangolin CoV MP789, bat-SL-CoVZC45 and bat-SL-CoVZXC21.

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An improved deep convolutional neural network architecture for chromosome abnormality detection using hybrid optimization model

Nimitha¹,

Ezhumalai²,

Chokkalingam³

2022

Microscopy Res & Technique

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Chromosomes are thread‐like structures located in the cell nucleus that contains the human body blueprint. Chromosome analysis is also known as karyotyping is the test taken to detect the abnormalities identified in the human chromosome. The two types of widely known chromosome abnormalities are structural and numerical abnormalities. Manual karyotyping is complex, time‐consuming, and error‐prone. To overcome these complexities, automated chromosome karyotype architecture is proposed using the deep convolutional neural network (DCNN) architecture. Training the DCNN architecture from scratch needs a huge dataset and to overcome this problem a generative adversarial networks is used to create adversarial samples that resemble the images in the actual dataset. The time‐consuming hyperparameter tuning in the DCNN architecture is overcome using the hybrid moth‐flame optimization integrated with the hill‐climbing strategy (HMFOHC). The HMFOHC algorithm is mainly utilized in this article to minimize the huge number of parameters associated with the DCNN architecture. The efficiency of the proposed methodology is evaluated using two datasets namely the BioImLab chromosome dataset and hospital dataset. The proposed HMFOHC optimized DCNN architecture is mainly utilized for multiclass classification where it differentiates five numerical chromosome abnormalities, namely Trisomy 13, Trisomy 18, Trisomy 21, Trisomy XXY syndrome, and Monosomy X. The proposed model offers an accuracy, F1‐score, and kappa coefficient value of 98.65%, 98.86%, and 0.9894, respectively. The results obtained show that the proposed model achieves higher classification accuracy when compared with the different state‐of‐art techniques such as deep learning, random forest, and CNN. The inference time of the proposed methodology is 12.5 s which is relatively lower than the state‐of‐art techniques. The proposed approach can help cytogenetics forensic experts make better decisions and save time by automating manual karyotyping. Research Highlights Manual karyotyping is complex, time‐consuming, and error‐prone. To overcome these complexities, automated chromosome karyotype architecture is proposed using the DCNN architecture The proposed method is mainly applied for multiclass classification where the different types of numerical abnormalities are addressed such as Trisomy 13, Trisomy 18, Trisomy 21, Trisomy XXY syndrome, and Monosomy X.

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New methodology for repetitive sequences identification in human X and Y chromosomes

Abstract: Graphical abstract

Cited by 7 publications

References 47 publications

Intelligent system based comparative analysis study of SARS-CoV-2 spike protein and antigenic proteins in different types of vaccines

Intelligent system based comparative analysis study of SARS-CoV-2 spike protein and antigenic proteins in different types of vaccines

Different genomic representations of novel pathogens base on signal processing algorithms: COVID-19 case study

An improved deep convolutional neural network architecture for chromosome abnormality detection using hybrid optimization model

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