Human polyomaviruses identification by logic mining techniques

Weitschek, Emanuel; Presti, Alessandra Lo; Drovandi, Guido; Felici, Giovanni; Ciccozzi, Massimo; Ciotti, Marco; Bertolazzi, Paola

doi:10.1186/1743-422x-9-58

Cited by 15 publications

(10 citation statements)

References 13 publications

(24 reference statements)

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“…A mathematical model of HBV transmission was used to predict future chronic hepatitis B (CHB) prevalence in the New Zealand Tongan population with different infection control strategies in literature (Thornley, Bullen & Roberts, 2008). Other studies have been performed with supervised methods for predicting viruses and pathologies (Weitschek et al, 2012; Weitschek, Cunial & Felici, 2015; Polychronopoulos et al, 2014). …”

Section: Introductionmentioning

confidence: 99%

Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models

Gan¹,

Chen²,

Huang³

2016

PeerJ

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This study compares and evaluates the prediction of hepatitis in Guangxi Province, China by using back propagation neural networks based genetic algorithm (BPNN-GA), generalized regression neural networks (GRNN), and wavelet neural networks (WNN). In order to compare the results of forecasting, the data obtained from 2004 to 2013 and 2014 were used as modeling and forecasting samples, respectively. The results show that when the small data set of hepatitis has seasonal fluctuation, the prediction result by BPNN-GA will be better than the two other methods. The WNN method is suitable for predicting the large data set of hepatitis that has seasonal fluctuation and the same for the GRNN method when the data increases steadily.

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Section: Introductionmentioning

confidence: 99%

Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models

Gan¹,

Chen²,

Huang³

2016

PeerJ

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“…, ; Weitschek et al . , ,b; van Velzen et al . ), and the analysis of numerical data such as gene expression profiles (Arisi et al .…”

Section: Feature Selectionmentioning

confidence: 99%

BLOG 2.0: a software system for character‐based species classification with DNA Barcode sequences. What it does, how to use it

Weitschek

Velzen

Felici

et al. 2013

Molecular Ecology Resources

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BLOG (Barcoding with LOGic) is a diagnostic and character-based DNA Barcode analysis method. Its aim is to classify specimens to species based on DNA Barcode sequences and on a supervised machine learning approach, using classification rules that compactly characterize species in terms of DNA Barcode locations of key diagnostic nucleotides. The BLOG 2.0 software, its fundamental modules, online/offline user interfaces and recent improvements are described. These improvements affect both methodology and software design, and lead to the availability of different releases on the website http://dmb.iasi.cnr.it/blog-downloads.php. Previous and new experimental tests show that BLOG 2.0 outperforms previous versions as well as other DNA Barcode analysis methods.

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“…The early region of BKPyV transcribes three transforming proteins called T antigens; LT antigen, ST antigen, and Truncated T antigen, whereas JCPyV early region encodes five T antigens; LT antigen, ST antigen, T’135, T’136 and T’165 antigens [10, 11]. The late region of both BKPyV and JCPyV encodes four proteins VP1, VP2, VP3 and agnoprotein.…”

Section: Introductionmentioning

confidence: 99%

Specific and quantitative detection of Human polyomaviruses BKPyV and JCPyV in the healthy Pakistani population

Hussain

Tasneem

Umer

et al. 2017

Virol J

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BackgroundThe BK Polyomavirus (BKPyV) and JC polyomavirus (JCPyV) infections are widespread in human population and have been associated with severe kidney and brain disorders, respectively. The viruses remain latent primarily in reno-urinary tract, reactivating only in case of a compromised immune system. The seroepidemiology and molecular prevalence of BKPyV and JCPyV have been widely studied both in healthy and immunocompromised patients worldwide. However, data regarding the prevalence of these viruses in the immunocompetent or apparently healthy Pakistani population is lacking. Herein, we present the first ever report on quantitative prevalence of BKPyV and JCPyV in the peripheral blood of a randomly selected cohort of healthy Pakistani population.MethodsA total of 266 whole blood samples were examined. The subjects were divided into three age groups: ≤ 25 years (young), 26–50 years (middle) and ≥ 51 years (elder). Absolute real time PCR assay was designed to quantify the BKPyV and JCPyV viral copy numbers in the range of 106 to 100 copies/mL.ResultsOverall, BKPyV was detected in 27.1% (72/266) individuals while JCPyV in 11.6% (31/266) indicating significant difference (p < 0.005) in the distribution of these two viruses. The prevalence of BKPyV significantly decreased from 51% (49/96) in young age group to 8.2% (7/85) in eldest age group. Whereas, JCPyV positivity rate slightly increased from 8.3% (8/96) in young age group to 11.8% (10/85) in elder age group. The median viral load was calculated as 6.2 log and 3.38 log copies/mL of blood for BKPyV and JCPyV, respectively. Notably, no significant difference in viral load of either of the subtypes was found between different age groups.ConclusionThe current study provides an important baseline data on the prevalence and viral load of circulating BKPyV and JCPyV in Pakistani population. The prevalence and viral load of BKPyV was comparatively higher than JCPyV. The prevalence of BKPyV significantly decreased with increase in age while JCPyV positivity rate slightly increased with increasing age. Viral load of both BKPyV and JCPyV was not correlated with the individual ages.Electronic supplementary materialThe online version of this article (doi:10.1186/s12985-017-0752-2) contains supplementary material, which is available to authorized users.

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Human polyomaviruses identification by logic mining techniques

Cited by 15 publications

References 13 publications

Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models

Comparisons of forecasting for hepatitis in Guangxi Province, China by using three neural networks models

BLOG 2.0: a software system for character‐based species classification with DNA Barcode sequences. What it does, how to use it

Specific and quantitative detection of Human polyomaviruses BKPyV and JCPyV in the healthy Pakistani population

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