Search results for: genetics data

Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer

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The purpose of the research is to explore some of the ways in which gameplay data can be analyzed to yield results that feedback into the learning ecosystem. Back-end data for all users as they played an MMOG, The Radix Endeavor, was collected, and this study reports the analyses on a specific genetics quest by using the data mining techniques, including the decision tree method. In the study, different reasons for quest failure between participants who eventually succeeded and who never succeeded were revealed. Regarding the in-game tools use, trait examiner was a key tool in the quest completion process. Subsequently, the results of decision tree showed that a lack of trait examiner usage can be made up with additional Punnett square uses, displaying multiple pathways to success in this quest. The methods of analysis used in this study and the resulting usage patterns indicate some useful ways that gameplay data can provide insights in two main areas. The first is for game designers to know how players are interacting with and learning from their game. The second is for players themselves as well as their teachers to get information on how they are progressing through the game, and to provide help they may need based on strategies and misconceptions identified in the data.

Keywords: MMOG, decision tree, genetics, gaming-learning interaction

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Authors: Aisling De Paor

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Scientific and technological developments are driving genetics and genetic technologies into the public sphere. Scientists are making genetic discoveries as to the make up of the human body and the cause and effect of disease, diversity and disability amongst individuals. Technological innovation in the field of genetics is also advancing, with the development of genetic testing, and other emerging genetic technologies, including gene editing (which offers the potential for genetic modification). In addition to the benefits for medicine, health care and humanity, these genetic advances raise a range of ethical, legal and societal concerns. From an ethical perspective, such advances may, for example, change the concept of humans and what it means to be human. Science may take over in conceptualising human beings, which may push the boundaries of existing human rights. New genetic technologies, particularly gene editing techniques create the potential to stigmatise disability, by highlighting disability or genetic difference as something that should be eliminated or anticipated. From a disability perspective, use (and misuse) of genetic technologies raise concerns about discrimination and violations to the dignity and integrity of the individual. With an acknowledgement of the likely future orientation of genetic science, and in consideration of the intersection of genetics and disability, this paper highlights the main concerns raised as genetic science and technology advances (particularly with gene editing developments), and the consequences for disability and human rights. Through the use of traditional doctrinal legal methodologies, it investigates the use (and potential misuse) of gene editing as creating the potential for a unique form of discrimination and stigmatization to develop, as well as a potential gateway to a form of new, subtle eugenics. This article highlights the need to maintain caution as to the use, application and the consequences of genetic technologies. With a focus on the law and policy position in Europe, it examines the need to control and regulate these new technologies, particularly gene editing. In addition to considering the need for regulation, this paper highlights non-normative approaches to address this area, including awareness raising and education, public discussion and engagement with key stakeholders in the field and the development of a multifaceted genetics advisory network.

Keywords: disability, gene-editing, genetics, law, regulation

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Authors: Luz Estrada

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The currents of evolutionary materialistic thought have argued that knowledge about an object is not obtained through the abstractive method. That is, the object cannot come to be understood if founded upon itself, nor does it take place by the encounter between form and matter. According to this affirmation, the research presented here identified as a problematic situation the absence of comprehension of the formal creation as a generative operation. This has been referred to as a recurrent lack in the production of objects and corresponds to the need to conceive the configurative process from the reality of its genesis. In this case, it is of interest to explore ways of creation that consider the object as if it were a living organism, as well as responding to the object’s experience as embodied in the designer since it unfolds its genesis simultaneously to the ways of existence of those who are involved in the generative experience.

Keywords: architecture, theoretical graphics, evolutionary genetics, formal perception

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Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

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Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

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Authors: Junghwa An, Sungkyoung Choi, Eun Ye, San Hoon Han, Young-Gun Choi, Chul Oun Jung

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The copper-winged bat (Myotis rufoniger) is the widely distributed medium body-sized bat in Asia, including Korea. This bat population has been decreasing because of habitat loss. This study reported the isolation and characterization of ten polymorphic microsatellite loci in endangered M. rufoniger. To do genetic studies, we use saliva DNA of bats during winter sleep period. The number of alleles per locus ranged from 2 to 9, and the observed and expected heterozygosities ranged from 0.063 to 0.750 and from 0.063 to 0.865, respectively. The average polymorphic information content (PIC) value of these markers was 0.37. Two loci of M. rufoniger showed departure from Hardy-Weinberg equilibrium(HWE). This demonstrated that the ten microsatellite loci can be used as genetic markers for further investigation of the copper-winged bat.

Keywords: copper-winged bat, microsatellite, population genetics, South Korea

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Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

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Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: database, forensic genetics, genetic analysis, sample management, software solution

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Authors: Wesley H. Brewer, John C. Sanford

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SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.

Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics

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Authors: Jarmila Bernasovska, Pavel Ružbarský, Ivan Bernasovsky, Regina Lohajová Behulová

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The paper presents the results of the application of molecular genetics methods in sport research, with special emphasis on the most advanced methods and trends in diagnosing of motoric predispositions for the sake of identifying talented children. Genetic tests differ in principle from the traditional motoric tests, because the DNA of an individual does not change during life. Genetics is important in determining the capacity of an individual and for professional sport level. Genetic information can be used for individual genetic predispositions in early childhood. The phenotypes are influenced by a combination of genetic and environmental factors. The aim of the presented study was to examine physical condition, coordination skills, motoric docility and to determine the frequency of ACTN3 (R577X) gene in Romany children from Eastern Slovakia and compared their motoric performance with non-Romany children. This paper is not looking just for a performance, but also its association to genetic predispositions in relation to ACTN3 gene and its R577X polymorphism. Genotype data were obtained from 175 Romany children from 6 to 15 years old and 218 non-Romany children at the same age from Eastern Slovakia. Biological material for genetic analyses comprised samples of buccal swabs. Genotypes were determined using Real Time High resolution melting PCR method (Rotor Gene 6000 Corbett and LightCycler 480 Roche). Romany children of analyzed group legged to non-Romany children at the same age in all the compared tests. The % distribution of R and X alleles in children was different from controls. The frequency of XX genotype was 11,45% which is comparable to a frequency of an Indian population. Data were analysed with the ANOVA statistical programme and parametric and nonparametric tests. This work was supported by grants APVV-0716-10, ITMS 26220120023 and ITMS 26220120041.

Keywords: ACTN3 gene, R577X polymorphism, Romany children, sport performance, Slovakia

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Authors: Masoud Sheidai

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Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

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Authors: Salma M. Wakil

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Advances in the field of genetics overwhelmed detecting large number of inherited disorders at the molecular level and directed to the development of innovative technologies. These innovations have led to gene sequencing, prenatal mutation detection, pre-implantation genetic diagnosis; population based carrier screening and genome wide analyses using microarrays. Microarrays are widely used in establishing clinical and diagnostic setup for genetic anomalies at a massive level, with the advent of cytoscan molecular karyotyping as a clinical utility card for detecting chromosomal aberrations with high coverage across the entire human genome. Unlike a regular karyotype that relies on the microscopic inspection of chromosomes, molecular karyotyping with cytoscan constructs virtual chromosomes based on the copy number analysis of DNA which improves its resolution by 100-fold. We have been investigating a large number of patients with Developmental Delay and Intellectual disability with this platform for establishing micro syndrome deletions and have detected number of novel CNV’s in the Arabian population with the clinical relevance.

Keywords: microarrays, molecular karyotyping, developmental delay, genetics

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Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

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Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Amir Bastani

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The result of the research in the field of human behavioural genetics demonstrates a genetic contribution of behavioural differences in aggression, violence, drug and substance abuse, antisocial personality disorder and other related traits. As the field of human behavioural genetics progresses and achieves credibility, the criminal accused continue to use its types of evidence into the criminal law. One of the most important genetic factors which controls certain neurotransmitters like dopamine and serotonin is the Monoamine Oxidase Acid A (MAOA) gene, known as the 'warrior gene'. The high-profile study by Caspi and colleagues in 2002 showed that the combination between one type of variation of the MAOA gene and childhood maltreatment noticeably predisposes a person to antisocial behaviour. Moreover, further scientific research shows that individuals with the MAOA gene have to some degree difficulties in controlling their impulses. Based on the evidence of MAOA, some criminal accused claimed difficulties in self-control. In the first case – the famous case of Mobley – the court rejected the MAOA evidence on the ground of the lack of scientific support. In contrast, in other cases after the Mobley trial, courts accepted the evidence of MAOA. In this paper, the issue of lack of impulse control produced by the MAOA gene and cases which relied on the MAOA evidence and successfully being accepted will be reviewed in detail. Finally, the anticipation of the paper for the future use of the MAOA evidence in criminal cases will be presented.

Keywords: genetic defence, criminal responsibility, MAOA, self-control

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Authors: Yasaman Mohammadi

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Executive functions are a critical component of goal-directed behavior, encompassing a diverse set of cognitive processes such as working memory, cognitive flexibility, and inhibitory control. These functions are known to decline with age, but the precise mechanisms underlying this decline remain unclear. This paper provides an in-depth review of recent research investigating age-related changes in executive functions, drawing on insights from neuroimaging, genetics, and cognitive neuroscience. Through an interdisciplinary approach, this paper offers a nuanced understanding of the complex interplay between neural mechanisms, genetic factors, and cognitive processes that contribute to executive function decline in aging. Here, we investigate how different neuroimaging methods, like functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), have helped scientists better understand the brain bases for age-related declines in executive function. Additionally, we discuss the role of genetic factors in mediating individual differences in executive functions across the lifespan, as well as the potential for cognitive interventions to mitigate age-related decline. Overall, this paper presents a comprehensive and integrative view of the current state of knowledge regarding age-related changes in executive functions. It underscores the need for continued interdisciplinary research to fully understand the complex and dynamic nature of executive function decline in aging, with the ultimate goal of developing effective interventions to promote healthy cognitive aging.

Keywords: executive functions, aging, neuroimaging, cognitive neuroscience, working memory, cognitive training

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Authors: Mohamed Thani Ibouroi, Ali Cheha, Claudine Montgelard, Veronique Arnal, Dawiyat Massoudi, Guillelme Astruc, Said Ali Ousseni Dhurham, Aurelien Besnard

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The Livingstone's flying fox (Pteropus livingstonii) and the Comorian fruit bat (P.seychellensis comorensis) are two endemic fruit bat species among the mostly threatened animals of the Comoros archipelagos. Despite their role as important ecosystem service providers like all flying fox species as pollinators and seed dispersers, little is known about their ecologies, population genetics and structures making difficult the development of evidence-based conservation strategies. In this study, we assess spatial distribution and ecological niche of both species using Species Distribution Modeling (SDM) based on the recent Ensemble of Small Models (ESMs) approach using presence-only data. Population structure and genetic diversity of the two species were assessed using both mitochondrial and microsatellite markers based on non-invasive genetic samples. Our ESMs highlight a clear niche partitioning of the two sympatric species. Livingstone’s flying fox has a very limited distribution, restricted on steep slope of natural forests at high elevation. On the contrary, the Comorian fruit bat has a relatively large geographic range spread over low elevations in farmlands and villages. Our genetic analysis shows a low genetic diversity for both fruit bats species. They also show that the Livingstone’s flying fox population of the two islands were genetically isolated while no evidence of genetic differentiation was detected for the Comorian fruit bats between islands. Our results support the idea that natural habitat loss, especially the natural forest loss and fragmentation are the important factors impacting the distribution of the Livingstone’s flying fox by limiting its foraging area and reducing its potential roosting sites. On the contrary, the Comorian fruit bats seem to be favored by human activities probably because its diets are less specialized. By this study, we concluded that the Livingstone’s flying fox species and its habitat are of high priority in term of conservation at the Comoros archipelagos scale.

Keywords: Comoros islands, ecological niche, habitat loss, population genetics, fruit bats, conservation biology

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Authors: Bawa Yusuf Muhammad, Musa Abubakar Kana, Aminatu Abdulrahman, Kerry Goetz

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Background: Inherited eye diseases are disorders that affect globally, 1 in 1000 people. The six main world populations have created databases containing information on eye genotypes. Aim: The aim of the scoping review was to mine and present the available information to date on the genetics of inherited eye diseases within the African continent. Method: Literature Search Strategy was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PubMed and Google Scholar searched for articles on inherited eye diseases from inception to 20th June 2022. Both Original and review articles that report on inherited, genetic or developmental/congenital eye diseases within the African Continent were included in the research. Results: A total of 1162 citations were obtained, but only 37 articles were reviewed based on the inclusion and exclusion criteria. The highest output of publications on inherited eye diseases comes from South Africa and Tunisia (about 43%), followed by Morocco and Egypt (27%), then Sub-Saharan Africa and North Africa (13.50%), while the remaining articles (16.5%) originated from Nigeria, Ghana, Mauritania Cameroon, Zimbabwe and combined article between Zimbabwe and Cameroon. Glaucoma and inherited retinal disorders represent the most studied diseases, followed by Albinism and congenital cataracts, respectively. Conclusion: Despite the growing research from Tunisia, Morocco, Egypt and South Africa, Sub-Saharan Africa remains almost a virgin region to explore the genetics of eye diseases.

Keywords: inherited eye diseases, Africa, scoping review, longitudinal eye study

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Authors: Chen Wang, Jared Evans, Yan Asmann

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With the quick evolvement of next-generation sequencing techniques, whole-exome or exome-panel data have become a cost-effective way for detection of small exonic mutations, but there has been a growing desire to accurately detect copy number variations (CNVs) as well. In order to address this research and clinical needs, we developed a sequencing coverage pattern-based method not only for copy number detections, data integrity checks, CNV calling, and visualization reports. The developed methodologies include complete automation to increase usability, genome content-coverage bias correction, CNV segmentation, data quality reports, and publication quality images. Automatic identification and removal of poor quality outlier samples were made automatically. Multiple experimental batches were routinely detected and further reduced for a clean subset of samples before analysis. Algorithm improvements were also made to improve somatic CNV detection as well as germline CNV detection in trio family. Additionally, a set of utilities was included to facilitate users for producing CNV plots in focused genes of interest. We demonstrate the somatic CNV enhancements by accurately detecting CNVs in whole exome-wide data from the cancer genome atlas cancer samples and a lymphoma case study with paired tumor and normal samples. We also showed our efficient reuses of existing exome sequencing data, for improved germline CNV calling in a family of the trio from the phase-III study of 1000 Genome to detect CNVs with various modes of inheritance. The performance of the developed method is evaluated by comparing CNV calling results with results from other orthogonal copy number platforms. Through our case studies, reuses of exome sequencing data for calling CNVs have several noticeable functionalities, including a better quality control for exome sequencing data, improved joint analysis with single nucleotide variant calls, and novel genomic discovery of under-utilized existing whole exome and custom exome panel data.

Keywords: bioinformatics, computational genetics, copy number variations, data reuse, exome sequencing, next generation sequencing

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Authors: Nadzeya Marozkina, Joe Zein, Benjamin Gaston

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Introduction: We have observed that many patients with Primary Ciliary Dyskinesia (PCD) benefit from asthma medications. In healthy airways, the ciliary function is normal. Antigens and irritants are rapidly cleared, and NO enters the gas phase normally to be exhaled. In the PCD airways, however, antigens, such as Dermatophagoides, are not as well cleared. This defect leads to oxidative stress, marked by increased DUOX1 expression and decreased superoxide dismutase [SOD] activity (manuscript under revision). H₂O₂, in high concentrations in the PCD airway, injures the airway. NO is oxidized rather than being exhaled, forming cytotoxic peroxynitrous acid. Thus, antigen stasis on PCD airway epithelium leads to airway injury and may predispose PCD patients to asthma. Indeed, recent population genetics suggest that PCD genes may be associated with asthma. We therefore hypothesized that PCD patients would be predisposed to having asthma. Methods. We analyzed our database of 18 million individual electronic medical records (EMRs) in the Indiana Network for Patient Care research database (INPCR). There is not an ICD10 code for PCD itself; code Q34.8 is most commonly used clinically. To validate analysis of this code, we queried patients who had an ICD10 code for both bronchiectasis and situs inversus totalis in INPCR. We also studied a validation cohort using the IBM Explorys® database (over 80 million individuals). Analyses were adjusted for age, sex and race using a 1 PCD: 3 controls matching method in INPCR and multivariable logistic regression in the IBM Explorys® database. Results. The prevalence of asthma ICD10 codes in subjects with a code Q34.8 was 67% vs 19% in controls (P < 0.0001) (Regenstrief Institute). Similarly, in IBM*Explorys, the OR [95% CI] for having asthma if a patient also had ICD10 code 34.8, relative to controls, was =4.04 [3.99; 4.09]. For situs inversus alone the OR [95% CI] was 4.42 [4.14; 4.71]; and bronchiectasis alone the OR [95% CI] =10.68 (10.56; 10.79). For both bronchiectasis and situs inversus together, the OR [95% CI] =28.80 (23.17; 35.81). Conclusions: PCD causes antigen stasis in the human airway (under review), likely predisposing to asthma in addition to oxidative and nitrosative stress and to airway injury. Here, we show that, by several different population-based metrics, and using two large databases, patients with PCD appear to have between a three- and 28-fold increased risk of having asthma. These data suggest that additional studies should be undertaken to understand the role of ciliary dysfunction in the pathogenesis and genetics of asthma. Decreased antigen clearance caused by ciliary dysfunction may be a risk factor for asthma development.

Keywords: antigen, PCD, asthma, nitric oxide

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: Masoud Sheidaei, Melica Tabasi, Fahimeh Koohdar, Mona Sheidaei

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Juglans regia L. is an economically important species of edible nuts. Iran is known as a center of origin of genetically rich walnut germplasm and expected to be found a large diversity within Iranian walnut populations. A detailed population genetic of local populations is useful for developing an optimal strategy for in situ conservation and can assist the breeders in crop improvement programs. Different phylogenetic studies have been carried out in this genus, but none has been concerned with genetic changes associated with geographical divergence and the identification of adaptive SNPs. Therefore, we carried out the present study to identify discriminating ITS nucleotides among Juglans species and also reveal association between ITS SNPs and geographical variables. We used different computations approaches like DAPC, CCA, and RDA analyses for the above-mentioned tasks. We also performed population genetics analyses for population effective size changes associated with the species expansion. The results obtained suggest that latitudinal distribution has a more profound effect on the species genetic changes. Similarly, multiple analytical approaches utilized for the identification of both discriminating DNA nucleotides/ SNPs almost produced congruent results. The SNPs with different phylogenetic importance were also identified by using a parsimony approach.

Keywords: Persian walnut, adaptive SNPs, data analyses, genetic diversity

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Authors: Abed Al-Bial, S. Alazazie, A. Shami

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The data were collected from 1992 to 2009 of White Boni sheep maintained at the Regional Research Station in the Central Highlands of Yemen. Data were analyzed to study the growth related traits and their genetic control. The least square means for body weights were 2.26±0.67, 11.14±0.46 and 19.21±1.25 kg for birth weight (BW), weaning weight (WW), six-month weight (WM6), respectively. The pre- and post-weaning average daily weight gains (ADG1 and ADG2) were 106.04±4.98g and 46.21±8.36 g/ day. Significant differences associated with the year of lambing were observed in body weight and weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and differences tended to increase with age. Single-born lambs had a distinct advantage over those born in twin births at all stages of growth. The lambs in the dam’s second to fourth parities were generally of heavier weight and higher daily weight gain than those in other parities. The heritabilities of all body weights, weight gains at different stages of growth were moderate (0.11-0.43). The phenotypic and genetic correlation among the different body weights were positive and high. The genetic correlations of the pre- and post-weaning average daily gains with body weights were hight to moderate, except BW with ADG2.

Keywords: breed, genetics, growth traits, heritability, sheep

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

Procedia PDF Downloads 534

Authors: I. Boroňová, J.Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, D. Gabriková, S. Mačeková

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Osteoporosis is a complex health disease characterized by low bone mineral density, which is determined by an interaction of genetics with metabolic and environmental factors. Current research in genetics of osteoporosis is focused on identification of responsible genes and polymorphisms. TNFRSF11B gene plays a key role in bone remodeling. The aim of this study was to investigate the genotype and allele distribution of A163G (rs3102735) osteoprotegerin gene promoter and G1181C (rs2073618) osteoprotegerin first exon polymorphisms in the group of 180 unrelated postmenopausal women with diagnosed osteoporosis and 180 normal controls. Genomic DNA was isolated from peripheral blood leukocytes using standard methodology. Genotyping for presence of different polymorphisms was performed using the Custom Taqman®SNP Genotyping assays. Hardy-Weinberg equilibrium was tested for each SNP in the groups of participants using the chi-square (χ2) test. The distribution of investigated genotypes in the group of patients with osteoporosis were as follows: AA (66.7%), AG (32.2%), GG (1.1%) for A163G polymorphism; GG (19.4%), CG (44.4%), CC (36.1%) for G1181C polymorphism. The distribution of genotypes in normal controls were follows: AA (71.1%), AG (26.1%), GG (2.8%) for A163G polymorphism; GG (22.2%), CG (48.9%), CC (28.9%) for G1181C polymorphism. In A163G polymorphism the variant G allele was more common among patients with osteoporosis: 17.2% versus 15.8% in normal controls. Also, in G1181C polymorphism the phenomenon of more frequent occurrence of C allele in the group of patients with osteoporosis was observed (58.3% versus 53.3%). Genotype and allele distributions showed no significant differences (A163G: χ2=0.270, p=0.605; χ2=0.250, p=0.616; G1181C: χ2= 1.730, p=0.188; χ2=1.820, p=0.177). Our results represents an initial study, further studies of more numerous file and associations studies will be carried out. Knowing the distribution of genotypes is important for assessing the impact of these polymorphisms on various parameters associated with osteoporosis. Screening for identification of “at-risk” women likely to develop osteoporosis and initiating subsequent early intervention appears to be most effective strategy to substantially reduce the risks of osteoporosis.

Keywords: osteoporosis, real-time PCR method, SNP polymorphisms

Procedia PDF Downloads 302

Authors: Nadia Obaed, Lexi Frankel, Amalia Ardeljan, Denis Nigel, Anniki Witter, Omar Rashid

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Breast cancer is the most common cancer among women, with a lifetime risk of one in eight of all women in the United States. Although breast cancer is prevalent throughout the world, the uneven distribution in incidence and mortality rates is shaped by the variation in population structure, environment, genetics and known lifestyle risk factors. Furthermore, the bacterial profile in healthy and cancerous breast tissue differs with a higher relative abundance of bacteria capable of causing DNA damage in breast cancer patients. Previous bacterial infections may change the composition of the microbiome and partially account for the environmental factors promoting breast cancer. One study found that higher amounts of Staphylococcus, Bacillus, and Enterobacteriaceae, of which Escherichia coli (E. coli) is a part, were present in breast tumor tissue. Based on E. coli’s ability to damage DNA, it is hypothesized that there is an increased risk of breast cancer associated with previous E. coli infection. Therefore, the purpose of this study was to evaluate the correlation between E. coli infection and the incidence of breast cancer. Holy Cross Health, Fort Lauderdale, provided access to the Health Insurance Portability and Accountability (HIPAA) compliant national database for the purpose of academic research. International Classification of Disease 9th and 10th Codes (ICD-9, ICD-10) was then used to conduct a retrospective analysis using data from January 2010 to December 2019. All breast cancer diagnoses and all patients infected versus not infected with E. coli that underwent typical E. coli treatment were investigated. The obtained data were matched for age, Charlson Comorbidity Score (CCI score), and antibiotic treatment. Standard statistical methods were applied to determine statistical significance and an odds ratio was used to estimate the relative risk. A total of 81286 patients were identified and analyzed from the initial query and then reduced to 31894 antibiotic-specific treated patients in both the infected and control group, respectively. The incidence of breast cancer was 2.51% and present in 2043 patients in the E. coli group compared to 5.996% and present in 4874 patients in the control group. The incidence of breast cancer was 3.84% and present in 1223 patients in the treated E. coli group compared to 6.38% and present in 2034 patients in the treated control group. The decreased incidence of breast cancer in the E. coli and treated E. coli groups was statistically significant with a p-value of 2.2x10-16 and 2.264x10-16, respectively. The odds ratio in the E. coli and treated E. coli groups was 0.784 and 0.787 with a 95% confidence interval, respectively (0.756-0.813; 0.743-0.833). The current study shows a statistically significant decrease in breast cancer incidence in association with previous Escherichia coli infection. Researching the relationship between single bacterial species is important as only up to 10% of breast cancer risk is attributable to genetics, while the contribution of environmental factors including previous infections potentially accounts for a majority of the preventable risk. Further evaluation is recommended to assess the potential and mechanism of E. coli in decreasing the risk of breast cancer.

Keywords: breast cancer, escherichia coli, incidence, infection, microbiome, risk

Procedia PDF Downloads 218

Authors: Safa A. Mohammed Ali, Ammar S. Ahamed, Mohammed Khair Abdalla

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The objectives of this study were to estimate the means and genetic parameters of birth and weaning weight of calves of pure Holstein-Friesian cows raised in Sudan. The traits studied were:*Weight at birth *Weight at weaning. The study also included some of the important factors that affected these traits. The data were analyzed using Harvey’s Least Squares and Maximum Likelihood programme. The results obtained showed that the overall mean weight at birth of the calves under study was 34.36±0.94kg. Male calves were found to be heavier than females; the difference between the sexes was highly significant (P<0.001). The mean weight at birth of male calves was 34.27±1.17 kg while that of females was 32.51±1.14kg. The effect of sex of calves, sire and parity of dam were highly significant (P<0.001). The overall mean of weight at weaning was 67.10 ± 5.05 kg, weight at weaning was significantly (p<0.001) effected by sex of calves, sire, year and season of birth have highly significant (P<0.001) effect on either trait. Also estimates heritabilities of birth weight was (0.033±0.015) lower than heritabilities of weaning weight (0.224±0.039), and genetic correlation was 0.563, the phenotypic correlation 0.281, and the environmental correlation 0.268.

Keywords: birth, weaning, weight, friesian

Procedia PDF Downloads 629

Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

Procedia PDF Downloads 370

Authors: Quyen Vu Dang Ha, Oanh Truong Thi, Thuoc Tran Linh, Kent Carpenter, Thinh Doan Vu, Binh Dang Thuy

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Enzyme restriction site associated DNA (EzRAD) has recently emerged as a promising genomic approach for exploring fish genetic diversity on a genome-wide scale. This is a simplified method for genomic genotyping in non-model organisms and applied for SNPs discovery in the population genetics of freshwater and marine fish in the South of Vietnam. The observations of regional-scale differentiation of commercial freshwater fish (smallscale croakers Boesemania microlepis) and marine fish (emperor Lethrinus lentjan) are clarified. Samples were collected along Hau River and coastal area in the south and center Vietnam. 52 DNA samples from Tra Vinh, An Giang Province for Boesemania microlepis and 34 DNA samples of Lethrinus lentjan from Phu Quoc, Nha Trang, Da Nang Province were used to prepare EzRAD libraries from genomic DNA digested with MboI and Sau3AI. A pooled sample of regional EzRAD libraries was sequenced using the HiSeq 2500 Illumina platform. For Boesemania microlepis, the small scale population different from upstream to downstream of Hau river were detected, An Giang population exhibited less genetic diversity (SNPs per individual from 14 to 926), in comparison to Tra Vinh population (from 11 to 2172). For Lethrinus lentjan, the result showed the minor difference between populations in the Northern and the Southern Mekong River. The numbers of contigs and SNPs vary from 1315 to 2455 and from 7122 to 8594, respectively (P ≤ 0.01). The current preliminary study reveals regional scale population disconnection probably reflecting environmental changing. Additional sampling and EzRad libraries need to be implemented for resource management in the Mekong Delta.

Keywords: Boesemania microlepis, EzRAD, Lethrinus lentjan, SNPs

Procedia PDF Downloads 468

Authors: Theertha Chandroth

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This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

Procedia PDF Downloads 86