scholarly journals HPV16-Genotyper: A Computational Tool for Risk-Assessment, Lineage Genotyping and Recombination Detection in HPV16 Sequences, Based on a Large-Scale Evolutionary Analysis

Diversity ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 497
Author(s):  
Marios Nikolaidis ◽  
Dimitris Tsakogiannis ◽  
Garyfalia Bletsa ◽  
Dimitris Mossialos ◽  
Christine Kottaridi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Large Scale ◽  
Distribution Patterns ◽  
Evolutionary Analysis ◽  
Entire Genome ◽  
Dna Viruses ◽  
Recombination Detection ◽  
Bioinformatics Study ◽  
Genomic Regions ◽  
Risk Of Cancer

Previous analyses have identified certain but limited evidence of recombination among HPV16 genomes, in accordance with a general perception that DNA viruses do not frequently recombine. In this evolutionary/bioinformatics study we have analyzed more than 3600 publicly available complete and partial HPV16 genomes. By studying the phylogenetic incongruence, similarity plots and the distribution patterns of lineage-specific SNPs, we identify several potential recombination events between the two major HPV16 evolutionary clades. These two clades comprise the (widely considered) phenotypically more benign (lower risk) lineage A and the (widely considered) phenotypically more aggressive (higher risk) non-European lineages B, C and D. We observe a frequency of potential recombinant sequences ranging between 0.3 and 1.2% which is low, but nevertheless considerable. Our findings have clinical implications and highlight that HPV16 genotyping and risk assessment based only on certain genomic regions and not the entire genome may provide a false genotype and, therefore, its associated risk estimate. Finally, based on this analysis, we have developed a bioinformatics tool that automates the entire process of HPV16 lineage genotyping, recombination detection and further identifies, within the submitted sequences, SNPs that have been reported in the literature to increase the risk of cancer.

scholarly journals Risk Assessment and Decision-Making Based on Mean-CVaR-Entropy for Flood Control Operation of Large Scale Reservoirs

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 649 ◽  
Author(s):  
Quansen Wang ◽  
Jianzhong Zhou ◽  
Kangdi Huang ◽  
Ling Dai ◽  
Gang Zha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Flood Control ◽  
Large Scale ◽  
Yangtze River Basin ◽  
Mean Value ◽  
Operation System ◽  
Control Operation ◽  
Flood Control Operation ◽  
Reservoir Flood Control Operation

The risk inevitably exists in the process of flood control operation and decision-making of reservoir group, due to the hydrologic and hydraulic uncertain factors. In this study different stochastic simulation methods were applied to simulate these uncertainties in multi-reservoir flood control operation, and the risk caused by different uncertainties was evaluated from the mean value, extreme value and discrete degree of reservoir occupied storage capacity under uncertain conditions. In order to solve the conflict between risk assessment indexes and evaluate the comprehensive risk of different reservoirs in flood control operation schemes, the subjective weight and objective weight were used to construct the comprehensive risk assessment index, and the improved Mahalanobis distance TOPSIS method was used to select the optimal flood control operation scheme. The proposed method was applied to the flood control operation system in the mainstream and its tributaries of upper reaches of the Yangtze River basin, and 14 cascade reservoirs were selected as a case study. The results indicate that proposed method can evaluate the risk of multi-reservoir flood control operation from all perspectives and provide a new method for multi-criteria decision-making of reservoir flood control operation, and it breaks the limitation of the traditional risk analysis method which only evaluated by risk rate and cannot evaluate the risk of the multi-reservoir flood control operation system.

scholarly journals Quantitative Risk Assessment for Deep Tunnel Failure Based on Normal Cloud Model: A Case Study at the ASHELE Copper Mine, China

2021 ◽  
Vol 11 (11) ◽  
pp. 5208
Author(s):  
Jianpo Liu ◽  
Hongxu Shi ◽  
Ren Wang ◽  
Yingtao Si ◽  
Dengcheng Wei ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Large Scale ◽  
Cloud Model ◽  
Quantitative Risk Assessment ◽  
Geological Condition ◽  
Deep Tunnel ◽  
Entropy Weight ◽  
Copper Mine ◽  
Evaluation Indexes ◽  
Metal Mines

The spatial and temporal distribution of tunnel failure is very complex due to geologic heterogeneity and variability in both mining processes and tunnel arrangement in deep metal mines. In this paper, the quantitative risk assessment for deep tunnel failure was performed using a normal cloud model at the Ashele copper mine, China. This was completed by considering the evaluation indexes of geological condition, mining process, and microseismic data. A weighted distribution of evaluation indexes was determined by implementation of an entropy weight method to reveal the primary parameters controlling tunnel failure. Additionally, the damage levels of the tunnel were quantitatively assigned by computing the degree of membership that different damage levels had, based on the expectation normalization method. The methods of maximum membership principle, comprehensive evaluation value, and fuzzy entropy were considered to determine the tunnel damage levels and risk of occurrence. The application of this method at the Ashele copper mine demonstrates that it meets the requirement of risk assessment for deep tunnel failure and can provide a basis for large-scale regional tunnel failure control in deep metal mines.

scholarly journals IGD: high-performance search for large-scale genomic interval datasets

2020 ◽  
Author(s):  
Jianglin Feng ◽  
Nathan C Sheffield
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Interval Data ◽  
Scale Analysis ◽  
Genome Database ◽  
Genomic Interval ◽  
Critical Resource ◽  
Genomic Regions ◽  
Genome Projects

Abstract Summary Databases of large-scale genome projects now contain thousands of genomic interval datasets. These data are a critical resource for understanding the function of DNA. However, our ability to examine and integrate interval data of this scale is limited. Here, we introduce the integrated genome database (IGD), a method and tool for searching genome interval datasets more than three orders of magnitude faster than existing approaches, while using only one hundredth of the memory. IGD uses a novel linear binning method that allows us to scale analysis to billions of genomic regions. Availability https://github.com/databio/IGD

scholarly journals Risk Assessment of Large-Scale Infrastructure Projects—Assumptions and Context

2020 ◽  
Vol 11 (1) ◽  
pp. 109
Author(s):  
Jana Korytárová ◽  
Vít Hromádka
Keyword(s):  
Risk Assessment ◽  
Economic Efficiency ◽  
Large Scale ◽  
Cash Flows ◽  
Statistical Characteristics ◽  
Individual Risk ◽  
Dependent Variables ◽  
Research Findings ◽  
Input Variables ◽  
Individual Risk Factors

This article deals with the partial outputs of large-scale infrastructure project risk assessment, specifically in the field of road and motorway construction. The Department of Transport spends a large amount of funds on project preparation and implementation, which however, must be allocated effectively, and with knowledge of the risks that may accompany them. Therefore, documentation for decision-making on project financing also includes their analysis. This article monitors the frequency of occurrence of individual risk factors within the qualitative risk analysis, with the support of the national risk register, and identifies dependent variables that represent part of the economic cash flows for determining project economic efficiency. At the same time, it compares these dependent variables identified by sensitivity analysis with critical variables, followed by testing the interaction of the critical variables’ effect on the project efficiency using the Monte Carlo method. A partial section of the research was focused on the analysis of the probability distribution of input variables, especially “the investment costs” and “time savings of infrastructure users” variables. The research findings conclude that it is necessary to pay attention to the setting of statistical characteristics of variables entering the economic efficiency indicator calculations, as the decision of whether or not to accept projects for funding is based on them.

scholarly journals Genetic variation in recombination rate in the pig

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Martin Johnsson ◽  
Andrew Whalen ◽  
Roger Ros-Freixedes ◽  
Gregor Gorjanc ◽  
Ching-Yi Chen ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Recombination Rate ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Genetic Material ◽  
A Genome ◽  
Pig Genome ◽  
Genetic Length ◽  
Trait Locus ◽  
Genomic Regions

Abstract Background Meiotic recombination results in the exchange of genetic material between homologous chromosomes. Recombination rate varies between different parts of the genome, between individuals, and is influenced by genetics. In this paper, we assessed the genetic variation in recombination rate along the genome and between individuals in the pig using multilocus iterative peeling on 150,000 individuals across nine genotyped pedigrees. We used these data to estimate the heritability of recombination and perform a genome-wide association study of recombination in the pig. Results Our results confirmed known features of the recombination landscape of the pig genome, including differences in genetic length of chromosomes and marked sex differences. The recombination landscape was repeatable between lines, but at the same time, there were differences in average autosome-wide recombination rate between lines. The heritability of autosome-wide recombination rate was low but not zero (on average 0.07 for females and 0.05 for males). We found six genomic regions that are associated with recombination rate, among which five harbour known candidate genes involved in recombination: RNF212, SHOC1, SYCP2, MSH4 and HFM1. Conclusions Our results on the variation in recombination rate in the pig genome agree with those reported for other vertebrates, with a low but nonzero heritability, and the identification of a major quantitative trait locus for recombination rate that is homologous to that detected in several other species. This work also highlights the utility of using large-scale livestock data to understand biological processes.

scholarly journals The association between XRCC3 rs1799794 polymorphism and cancer risk: a meta-analysis of 34 case–control studies

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Weiqing Liu ◽  
Shumin Ma ◽  
Lei Liang ◽  
Zhiyong Kou ◽  
Hongbin Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Thyroid Cancer ◽  
Cancer Risk ◽  
Large Scale ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Cancer Type ◽  
Increased Risk ◽  
Risk Of Cancer

Abstract Background Studies on the XRCC3 rs1799794 polymorphism show that this polymorphism is involved in a variety of cancers, but its specific relationships or effects are not consistent. The purpose of this meta-analysis was to investigate the association between rs1799794 polymorphism and susceptibility to cancer. Methods PubMed, Embase, the Cochrane Library, Web of Science, and Scopus were searched for eligible studies through June 11, 2019. All analyses were performed with Stata 14.0. Subgroup analyses were performed by cancer type, ethnicity, source of control, and detection method. A total of 37 studies with 23,537 cases and 30,649 controls were included in this meta-analysis. Results XRCC3 rs1799794 increased cancer risk in the dominant model and heterozygous model (GG + AG vs. AA: odds ratio [OR] = 1.04, 95% confidence interval [CI] = 1.00–1.08, P = 0.051; AG vs. AA: OR = 1.05, 95% CI = 1.00–1.01, P = 0.015). The existence of rs1799794 increased the risk of breast cancer and thyroid cancer, but reduced the risk of ovarian cancer. In addition, rs1799794 increased the risk of cancer in the Caucasian population. Conclusion This meta-analysis confirms that XRCC3 rs1799794 is related to cancer risk, especially increased risk for breast cancer and thyroid cancer and reduced risk for ovarian cancer. However, well-designed large-scale studies are required to further evaluate the results.

Mining wastewater management and its effects on groundwater and ecosystems

2014 ◽  
Vol 70 (9) ◽  
pp. 1481-1487 ◽  
Author(s):  
A. Celebi ◽  
S. Özdemir
Keyword(s):  
Risk Assessment ◽  
Best Management Practices ◽  
Large Scale ◽  
Management Practices ◽  
Developed Countries ◽  
International Standards ◽  
Wastewater Management ◽  
Mining Areas ◽  
Mining Wastewater ◽  
The Developed Countries

Large-scale mining activities have a huge impact on the environment. Determination of the size of the effect and monitoring it is vital. In this study, risk assessment studies in mining areas and the effect of mining on groundwater and ecosystems were investigated. Best management practices and risk assessment steps were determined, especially in areas with huge amounts of mining wastewater. The pollution of groundwater and its reaching humans is a risk of major importance. Our study showed, using many cases with different parameters and countries, that the management of mining wastewater is vital. Environmental impact assessments and monitoring studies must be carried out before operation and at the closure of the mine. Policies must be in place and ready to apply. Factors of climate, geology, ecology and human health must be considered over a long period. Currently, only the developed countries are applying policies and paying attention to the risk. International assessments and health risk assessments should be carried out according to international standards.

Technical Risk Assessment of Large-Scale Construction Project Based on Triangle Whitening Weight Function

2014 ◽  
Vol 989-994 ◽  
pp. 5294-5299
Author(s):  
Wei Ma
Keyword(s):  
Risk Assessment ◽  
Weight Function ◽  
Large Scale ◽  
Construction Project ◽  
Scale Construction ◽  
Assessment Model ◽  
Grey Theory ◽  
Risk Assessment Model ◽  
Technical Risk

Technical risk assessment model of large-scale construction project has been established by using triangle whitening weight function of grey theory against the problems of technical risk assessment of large-scale construction project. In the end, through example verification, this model is approved to be feasible and have certain value of reference and utilization in similar problems.

scholarly journals A NOTE ON PHASING LONG GENOMIC REGIONS USING LOCAL HAPLOTYPE PREDICTIONS

2006 ◽  
Vol 04 (03) ◽  
pp. 639-647 ◽  
Author(s):  
ELEAZAR ESKIN ◽  
RODED SHARAN ◽  
ERAN HALPERIN
Keyword(s):  
Large Scale ◽  
Computational Cost ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Novel Approach ◽  
Maximum Likelihood Criterion ◽  
The Common ◽  
Genomic Regions ◽  
High Computational Cost ◽  
Combining Information

The common approaches for haplotype inference from genotype data are targeted toward phasing short genomic regions. Longer regions are often tackled in a heuristic manner, due to the high computational cost. Here, we describe a novel approach for phasing genotypes over long regions, which is based on combining information from local predictions on short, overlapping regions. The phasing is done in a way, which maximizes a natural maximum likelihood criterion. Among other things, this criterion takes into account the physical length between neighboring single nucleotide polymorphisms. The approach is very efficient and is applied to several large scale datasets and is shown to be successful in two recent benchmarking studies (Zaitlen et al., in press; Marchini et al., in preparation). Our method is publicly available via a webserver at .

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