Recovery of Virus Samples from Various Surfaces with the Integrated Virus Detection System

2010 ◽  
Author(s):  
Charles H. Wick ◽  
Patrick E. McCubbin
Keyword(s):  
Detection System ◽  
Virus Detection

Mass Spectrometry and Integrated Virus Detection System Characterization of MS2 Bacteriophage

2005 ◽  
Author(s):  
Rabih E. Jabbour ◽  
Deborah Kuzmanovic ◽  
Patrick E. McCubbin ◽  
Ilya Elashvili ◽  
Charles H. Wick
Keyword(s):  
Mass Spectrometry ◽  
Detection System ◽  
Virus Detection ◽  
Ms2 Bacteriophage ◽  
System Characterization

Integrated Virus Detection System Characterization of MS2 and TBSV After Pulsed Lamp Exposure

2010 ◽  
Author(s):  
Charles H. Wick ◽  
Stephen Wengraitis ◽  
Patrick E. McCubbin
Keyword(s):  
Detection System ◽  
Virus Detection ◽  
System Characterization

scholarly journals Expression and Purification of Recombinant Mayaro Virus Envelope Glycoproteins E1 and E2 to Develop a Mayaro Virus Detection System

2020 ◽  
Vol 50 (1) ◽  
pp. 25
Author(s):  
So Yeon Yi ◽  
Kyungah Yoon ◽  
Jungsun Kwon ◽  
Kyoon Eon Kim ◽  
Kyoungsook Park ◽  
...  
Keyword(s):  
Detection System ◽  
Virus Detection ◽  
Envelope Glycoproteins ◽  
Expression And Purification ◽  
Virus Envelope ◽  
Mayaro Virus

scholarly journals MultiScan: A Private Online Virus Detection System

2019 ◽  
Vol 8 (6) ◽  
pp. 53-55
Author(s):  
Ming Liu ◽  
Yuxuan He ◽  
Zhi Xue ◽  
Xiangjian He ◽  
Jinjun Chen
Keyword(s):  
Detection System ◽  
Virus Detection

scholarly journals Non Invasive Detection of Dengue Viruses from Saliva: In vitro Study

2018 ◽  
Vol 22 (2) ◽  
pp. 75
Author(s):  
Budi Saksono
Keyword(s):  
Dengue Virus ◽  
Detection System ◽  
Point Of Care ◽  
Virus Detection ◽  
In Vitro Study ◽  
Vitro Study ◽  
Dengue Viruses ◽  
Non Invasive ◽  
Preliminary Study

      In the previous paper, we had succeeded in developing an early detection system of dengue viruses using Sugar liganded Gold Nano Particle (SGNP) only from 6 μL serum. It has been reported that dengue virus is also detected in the saliva and urine of the patient. The evidences lead to the possibility of developing non-invasive methods of dengue virus detection. In this in vitro study, we evaluated the utility of SGNP to capture and concentrate dengue virion in 10% saliva solution. The results showed that dengue virion was successfully detected in 10% of saliva solution. Analysis of virion stability during storage showed that virions in salivary samples were stable up to 3 days at temperature wherease the RNA has significantly degraded. Although still a preliminary study, the data obtained show the prospect of SGNP as a non-invasive dengue virus detection method, as well as the development of POC (Point of Care) method. Clinical trials using saliva from dengue viruses infected patients need to be done to prove the effectiveness of the SGNP method.

High-Performance Virus Detection System by using Deep Learning

2020 ◽  
Author(s):  
Ying-Feng Hsu ◽  
Makiko Ito ◽  
Takumi Maruyama ◽  
Morito Matsuoka ◽  
Nicolas Jung ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Performance ◽  
Detection System ◽  
Virus Detection

A Research of Virus Detection Combined Dynamic and Static Analysis Methods

2011 ◽  
Vol 187 ◽  
pp. 625-630
Author(s):  
Chun Yu Miao ◽  
Li Na Chen
Keyword(s):  
Neural Network ◽  
Static Analysis ◽  
Detection System ◽  
Probabilistic Neural Network ◽  
Virus Detection ◽  
Support Vector ◽  
Svm Classifier ◽  
Analysis Methods ◽  
Individual Classifier ◽  
Theory Of Evidence

we present a virus detection system based on the D-S theory of evidence, in which the dynamic and static analysis methods are combined. The detection engine applies two types of classifier, support vector amchine and probabilistic neural network to detect the virus. For SVM classifier, we extract the feature vector by monitoring the samples. And the static feature of samples is used in the probabilistic neural network classifier. Finally, the D-S theory of evidence is used to combine the contribution of each individual classifier to give the final decision.experiments show the presented method is more efficiently of the virus detections.

Sign in / Sign up

Export Citation Format

Share Document