scholarly journals Predicting the host of influenza viruses based on the word vector

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3579 ◽  
Author(s):  
Beibei Xu ◽  
Zhiying Tan ◽  
Kenli Li ◽  
Taijiao Jiang ◽  
Yousong Peng
Keyword(s):  
Dna Sequences ◽  
Influenza A ◽  
Rapid Determination ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Support Vector ◽  
Local Alignment ◽  
Svm Classifier ◽  
Early Assessment ◽  
Feature Extraction Method

Newly emerging influenza viruses continue to threaten public health. A rapid determination of the host range of newly discovered influenza viruses would assist in early assessment of their risk. Here, we attempted to predict the host of influenza viruses using the Support Vector Machine (SVM) classifier based on the word vector, a new representation and feature extraction method for biological sequences. The results show that the length of the word within the word vector, the sequence type (DNA or protein) and the species from which the sequences were derived for generating the word vector all influence the performance of models in predicting the host of influenza viruses. In nearly all cases, the models built on the surface proteins hemagglutinin (HA) and neuraminidase (NA) (or their genes) produced better results than internal influenza proteins (or their genes). The best performance was achieved when the model was built on the HA gene based on word vectors (words of three-letters long) generated from DNA sequences of the influenza virus. This results in accuracies of 99.7% for avian, 96.9% for human and 90.6% for swine influenza viruses. Compared to the method of sequence homology best-hit searches using the Basic Local Alignment Search Tool (BLAST), the word vector-based models still need further improvements in predicting the host of influenza A viruses.

A Structural Analysis Based Feature Extraction Method for OCR System For Myanmar Printed Document Images

2012 ◽  
Vol 2 (1) ◽  
pp. 16-41 ◽  
Author(s):  
Htwe Pa Pa Win ◽  
Phyo Thu Thu Khine ◽  
Khin Nwe Ni Tun
Keyword(s):  
Feature Extraction ◽  
Structural Analysis ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Extraction Method ◽  
Recognition Performance ◽  
Extraction Methods ◽  
Support Vector ◽  
Svm Classifier ◽  
Feature Extraction Method

This paper proposes a new feature extraction method for off-line recognition of Myanmar printed documents. One of the most important factors to achieve high recognition performance in Optical Character Recognition (OCR) system is the selection of the feature extraction methods. Different types of existing OCR systems used various feature extraction methods because of the diversity of the scripts’ natures. One major contribution of the work in this paper is the design of logically rigorous coding based features. To show the effectiveness of the proposed method, this paper assumed the documents are successfully segmented into characters and extracted features from these isolated Myanmar characters. These features are extracted using structural analysis of the Myanmar scripts. The experimental results have been carried out using the Support Vector Machine (SVM) classifier and compare the pervious proposed feature extraction method.

scholarly journals Aircraft Type Recognition in Remote Sensing Images Based on Feature Learning with Conditional Generative Adversarial Networks

2018 ◽  
Vol 10 (7) ◽  
pp. 1123 ◽  
Author(s):  
Yuhang Zhang ◽  
Hao Sun ◽  
Jiawei Zuo ◽  
Hongqi Wang ◽  
Guangluan Xu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Feature Extraction ◽  
Loss Function ◽  
Extraction Method ◽  
Generative Adversarial Networks ◽  
Support Vector ◽  
Svm Classifier ◽  
Feature Extraction Method ◽  
Adversarial Networks ◽  
Aircraft Type

Aircraft type recognition plays an important role in remote sensing image interpretation. Traditional methods suffer from bad generalization performance, while deep learning methods require large amounts of data with type labels, which are quite expensive and time-consuming to obtain. To overcome the aforementioned problems, in this paper, we propose an aircraft type recognition framework based on conditional generative adversarial networks (GANs). First, we design a new method to precisely detect aircrafts’ keypoints, which are used to generate aircraft masks and locate the positions of the aircrafts. Second, a conditional GAN with a region of interest (ROI)-weighted loss function is trained on unlabeled aircraft images and their corresponding masks. Third, an ROI feature extraction method is carefully designed to extract multi-scale features from the GAN in the regions of aircrafts. After that, a linear support vector machine (SVM) classifier is adopted to classify each sample using their features. Benefiting from the GAN, we can learn features which are strong enough to represent aircrafts based on a large unlabeled dataset. Additionally, the ROI-weighted loss function and the ROI feature extraction method make the features more related to the aircrafts rather than the background, which improves the quality of features and increases the recognition accuracy significantly. Thorough experiments were conducted on a challenging dataset, and the results prove the effectiveness of the proposed aircraft type recognition framework.

scholarly journals Molecular Characterization of Seasonal Influenza A and B from Hospitalized Patients in Thailand in 2018–2019

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 977
Author(s):  
Kobporn Boonnak ◽  
Chayasin Mansanguan ◽  
Dennis Schuerch ◽  
Usa Boonyuen ◽  
Hatairat Lerdsamran ◽  
...  
Keyword(s):  
Amino Acid ◽  
Influenza A ◽  
Seasonal Influenza ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Antigenic Drift ◽  
Influenza B ◽  
Receptor Binding Site ◽  
Antigenic Sites ◽  
Ha Protein

Influenza viruses continue to be a major public health threat due to the possible emergence of more virulent influenza virus strains resulting from dynamic changes in virus adaptability, consequent of functional mutations and antigenic drift in surface proteins, especially hemagglutinin (HA) and neuraminidase (NA). In this study, we describe the genetic and evolutionary characteristics of H1N1, H3N2, and influenza B strains detected in severe cases of seasonal influenza in Thailand from 2018 to 2019. We genetically characterized seven A/H1N1 isolates, seven A/H3N2 isolates, and six influenza B isolates. Five of the seven A/H1N1 viruses were found to belong to clade 6B.1 and were antigenically similar to A/Switzerland/3330/2017 (H1N1), whereas two isolates belonged to clade 6B.1A1 and clustered with A/Brisbane/02/2018 (H1N1). Interestingly, we observed additional mutations at antigenic sites (S91R, S181T, T202I) as well as a unique mutation at a receptor binding site (S200P). Three-dimensional (3D) protein structure analysis of hemagglutinin protein reveals that this unique mutation may lead to the altered binding of the HA protein to a sialic acid receptor. A/H3N2 isolates were found to belong to clade 3C.2a2 and 3C.2a1b, clustering with A/Switzerland/8060/2017 (H3N2) and A/South Australia/34/2019 (H3N2), respectively. Amino acid sequence analysis revealed 10 mutations at antigenic sites including T144A/I, T151K, Q213R, S214P, T176K, D69N, Q277R, N137K, N187K, and E78K/G. All influenza B isolates in this study belong to the Victoria lineage. Five out of six isolates belong to clade 1A3-DEL, which relate closely to B/Washington/02/2009, with one isolate lacking the three amino acid deletion on the HA segment at position K162, N163, and D164. In comparison to the B/Colorado/06/2017, which is the representative of influenza B Victoria lineage vaccine strain, these substitutions include G129D, G133R, K136E, and V180R for HA protein. Importantly, the susceptibility to oseltamivir of influenza B isolates, but not A/H1N1 and A/H3N2 isolates, were reduced as assessed by the phenotypic assay. This study demonstrates the importance of monitoring genetic variation in influenza viruses regarding how acquired mutations could be associated with an improved adaptability for efficient transmission.

scholarly journals Evolutionary, genetic, structural characterization and its functional implications for the influenza A (H1N1) infection outbreak in India from 2009 to 2017

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sara Jones ◽  
Shijulal Nelson-Sathi ◽  
Yejun Wang ◽  
Raji Prasad ◽  
Sabrina Rayen ◽  
...  
Keyword(s):  
Influenza A ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Antigenic Drift ◽  
Global Perspective ◽  
Global Circulation ◽  
Influenza A H1n1 ◽  
Indian Isolates ◽  
H1n1 Strain ◽  
The Tropics

Abstract Influenza A (H1N1) continues to be a major public health threat due to possible emergence of a more virulent H1N1 strain resulting from dynamic changes in virus adaptability consequent to functional mutations and antigenic drift in the hemagglutinin (HA) and neuraminidase (NA) surface proteins. In this study, we describe the genetic and evolutionary characteristics of H1N1 strains that circulated in India over a period of nine years from 2009 to 2017 in relation to global strains. The finding is important from a global perspective since previous phylogenetic studies have suggested that the tropics contributed substantially to the global circulation of influenza viruses. Bayesian phylogenic analysis of HA sequences along with global strains indicated that there is a temporal pattern of H1N1 evolution and clustering of Indian isolates with globally circulating strains. Interestingly, we observed four new amino acid substitutions (S179N, I233T, S181T and I312V) in the HA sequence of H1N1 strains isolated during 2017 and two (S181T and I312V) were found to be unique in Indian isolates. Structurally these two unique mutations could lead to altered glycan specificity of the HA gene. Similarly, sequence and structural analysis of NA domain revealed that the presence of K432E mutation in H1N1 strains isolated after 2015 from India and in global strains found to induce a major loop shift in the vicinity of the catalytic site. The findings presented here offer an insight as to how these acquired mutations could be associated to an improved adaptability of the virus for efficient human transmissibility.

scholarly journals Modified Sialic Acids on Mucus and Erythrocytes Inhibit Influenza A Virus Hemagglutinin and Neuraminidase Functions

2020 ◽  
Vol 94 (9) ◽  
Author(s):  
Karen N. Barnard ◽  
Brynn K. Alford-Lawrence ◽  
David W. Buchholz ◽  
Brian R. Wasik ◽  
Justin R. LaClair ◽  
...  
Keyword(s):  
Influenza A Virus ◽  
Influenza A ◽  
Protective Role ◽  
Sialic Acids ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Clear Understanding ◽  
Cellular Functions ◽  
Acetylneuraminic Acid ◽  
Mouse Tissues

ABSTRACT Sialic acids (Sia) are the primary receptors for influenza viruses and are widely displayed on cell surfaces and in secreted mucus. Sia may be present in variant forms that include O-acetyl modifications at C-4, C-7, C-8, and C-9 positions and N-acetyl or N-glycolyl at C-5. They can also vary in their linkages, including α2-3 or α2-6 linkages. Here, we analyze the distribution of modified Sia in cells and tissues of wild-type mice or in mice lacking CMP-N-acetylneuraminic acid hydroxylase (CMAH) enzyme, which synthesizes N-glycolyl (Neu5Gc) modifications. We also examined the variation of Sia forms on erythrocytes and in saliva from different animals. To determine the effect of Sia modifications on influenza A virus (IAV) infection, we tested for effects on hemagglutinin (HA) binding and neuraminidase (NA) cleavage. We confirmed that 9-O-acetyl, 7,9-O-acetyl, 4-O-acetyl, and Neu5Gc modifications are widely but variably expressed in mouse tissues, with the highest levels detected in the respiratory and gastrointestinal (GI) tracts. Secreted mucins in saliva and surface proteins of erythrocytes showed a high degree of variability in display of modified Sia between different species. IAV HAs from different virus strains showed consistently reduced binding to both Neu5Gc- and O-acetyl-modified Sia; however, while IAV NAs were inhibited by Neu5Gc and O-acetyl modifications, there was significant variability between NA types. The modifications of Sia in mucus may therefore have potent effects on the functions of IAV and may affect both pathogens and the normal flora of different mucosal sites. IMPORTANCE Sialic acids (Sia) are involved in numerous different cellular functions and are receptors for many pathogens. Sia come in chemically modified forms, but we lack a clear understanding of how they alter interactions with microbes. Here, we examine the expression of modified Sia in mouse tissues, on secreted mucus in saliva, and on erythrocytes, including those from IAV host species and animals used in IAV research. These Sia forms varied considerably among different animals, and their inhibitory effects on IAV NA and HA activities and on bacterial sialidases (neuraminidases) suggest a host-variable protective role in secreted mucus.

scholarly journals Structural and Molecular Characterization of the Hemagglutinin from the Fifth-Epidemic-Wave A(H7N9) Influenza Viruses

2018 ◽  
Vol 92 (16) ◽  
Author(s):  
Hua Yang ◽  
Paul J. Carney ◽  
Jessie C. Chang ◽  
Zhu Guo ◽  
James Stevens
Keyword(s):  
Public Health ◽  
Avian Influenza ◽  
Influenza A ◽  
Human Infection ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Health Concern ◽  
Public Health Concern ◽  
H7n9 Influenza ◽  
Epidemic Wave

ABSTRACTThe avian influenza A(H7N9) virus continues to cause human infections in China and is a major ongoing public health concern. Five epidemic waves of A(H7N9) infection have occurred since 2013, and the recent fifth epidemic wave saw the emergence of two distinct lineages with elevated numbers of human infection cases and broader geographic distribution of viral diseases compared to the first four epidemic waves. Moreover, highly pathogenic avian influenza (HPAI) A(H7N9) viruses were also isolated during the fifth epidemic wave. Here, we present a detailed structural and biochemical analysis of the surface hemagglutinin (HA) antigen from viruses isolated during this recent epidemic wave. Results highlight that, compared to the 2013 virus HAs, the fifth-wave virus HAs remained a weak binder to human glycan receptor analogs. We also studied three mutations, V177K-K184T-G219S, that were recently reported to switch a 2013 A(H7N9) HA to human-type receptor specificity. Our results indicate that these mutations could also switch the H7 HA receptor preference to a predominantly human binding specificity for both fifth-wave H7 HAs analyzed in this study.IMPORTANCEThe A(H7N9) viruses circulating in China are of great public health concern. Here, we report a molecular and structural study of the major surface proteins from several recent A(H7N9) influenza viruses. Our results improve the understanding of these evolving viruses and provide important information on their receptor preference that is central to ongoing pandemic risk assessment.

Influenza viruses: transmission between species

1980 ◽  
Vol 288 (1029) ◽  
pp. 439-447 ◽  
Keyword(s):  
Influenza A ◽  
Direct Evidence ◽  
Swine Influenza ◽  
Indirect Evidence ◽  
Preliminary Evidence ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Aquatic Birds ◽  
Influenza A Viruses ◽  
Wide Range

The only direct evidence for transmission of influenza viruses between species comes from studies on swine influenza viruses. Antigenically and genetically identical Hsw1N1 influenza viruses were isolated from pigs and man on the same farm in Wisconsin, U.S.A. The isolation of H3N2 influenza viruses from a wide range of lower animals and birds suggests that influenza viruses of man can spread to the lower orders. Under some conditions the H3N2 viruses can persist for a number of years in some species. The isolation, from aquatic birds, of a large number of influenza A viruses that possess surface proteins antigenically similar to the viruses isolated from man, pigs and horses provides indirect evidence for inter-species transmission. There is now a considerable body of evidence which suggests that influenza viruses of lower animals and birds may play a role in the origin of some of the pandemic strains of influenza A viruses. There is no direct evidence that the influenza viruses in aquatic birds are transmitted to man, but they may serve as a genetic pool from which some genes may be introduced into humans by recombination. Preliminary evidence suggests that the molecular basis of host range and virulence may be related to the RNA segments coding for one of the polymerase proteins (P3) and for the nucleoprotein (NP).

scholarly journals Fast Pedestrian Recognition Based on Multisensor Fusion

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Hongyu Hu ◽  
Zhaowei Qu ◽  
Zhihui Li ◽  
Jinhui Hu ◽  
Fulu Wei
Keyword(s):  
Region Of Interest ◽  
Recognition Algorithm ◽  
Support Vector ◽  
Svm Classifier ◽  
Multisensor Fusion ◽  
Feature Extraction Method ◽  
Urban Road ◽  
Histograms Of Oriented Gradients ◽  
Large Numbers ◽  
Candidate Regions

A fast pedestrian recognition algorithm based on multisensor fusion is presented in this paper. Firstly, potential pedestrian locations are estimated by laser radar scanning in the world coordinates, and then their corresponding candidate regions in the image are located by camera calibration and the perspective mapping model. For avoiding time consuming in the training and recognition process caused by large numbers of feature vector dimensions, region of interest-based integral histograms of oriented gradients (ROI-IHOG) feature extraction method is proposed later. A support vector machine (SVM) classifier is trained by a novel pedestrian sample dataset which adapt to the urban road environment for online recognition. Finally, we test the validity of the proposed approach with several video sequences from realistic urban road scenarios. Reliable and timewise performances are shown based on our multisensor fusing method.

scholarly journals The effects of modified sialic acids on mucus and erythrocytes on influenza A virus HA and NA functions

2019 ◽  
Author(s):  
Karen N. Barnard ◽  
Brynn K. Alford-Lawrence ◽  
David W. Buchholz ◽  
Brian R. Wasik ◽  
Justin R. LaClair ◽  
...  
Keyword(s):  
Influenza A Virus ◽  
Influenza A ◽  
Protective Role ◽  
Sialic Acids ◽  
Influenza Viruses ◽  
Surface Proteins ◽  
Clear Understanding ◽  
Cellular Functions ◽  
Acetylneuraminic Acid ◽  
Mouse Tissues

ABSTRACTSialic acids (Sia) are the primary receptors for influenza viruses, and are widely displayed on cell surfaces and in secreted mucus. Sia may be present in variant forms that include O-acetyl modifications at C4, C7, C8, and C9 positions, and N-acetyl or N-glycolyl at C5. They can also vary in their linkages, including α2-3 or α2-6-linkages. Here, we analyzed the distribution of modified Sia in cells and tissues of wild-type mice, or in mice lacking cytidine 5’-monophosphate-N-acetylneuraminic acid hydroxylase (CMAH) enzyme that synthesizes N-glycolyl modifications (Neu5Gc). We also examined the variation of Sia forms on erythrocytes and saliva from different animals. To determine the effect of Sia modifications on influenza A virus (IAV) infection, we tested for effects on hemagglutinin (HA) binding and neuraminidase (NA) cleavage. We confirmed that 9-O-acetyl, 7,9-O-acetyl, 4-O-acetyl, and Neu5Gc modifications are widely but variably expressed in mouse tissues, with the highest levels detected in the respiratory and gastrointestinal tracts. Secreted mucins in saliva and surface proteins of erythrocytes showed a great degree of variability in display of modified Sia between different species. IAV HA from different virus strains showed consistently reduced binding to both Neu5Gc and O-acetyl modified Sia; however, while IAV NA were inhibited by Neu5Gc and O-acetyl modifications, there was significant variability between NA types. The modifications of Sia in mucus may therefore have potent effects on the functions of IAV, and may affect both pathogens and the normal flora of different mucosal sites.IMPORTANCESialic acids (Sia) are involved in many different cellular functions and are receptors for many pathogens. Sia come in many chemically modified forms but we lack a clear understanding of how they alter the interactions with microbes. Here we examine the expression of modified Sia in mouse tissues, on secreted mucus in saliva, and on erythrocytes, including those from IAV host species and animals used in IAV research. These Sia forms varied considerably between different animals, and their inhibitory effects on IAV NA and HA activities and on bacterial sialidases (neuraminidases) suggest a host-variable protective role in secreted mucus.

scholarly journals A Feature Extraction Method of Ship-Radiated Noise Based on Fluctuation-Based Dispersion Entropy and Intrinsic Time-Scale Decomposition

Entropy ◽  
2019 ◽  
Vol 21 (7) ◽  
pp. 693 ◽  
Author(s):  
Zhaoxi Li ◽  
Yaan Li ◽  
Kai Zhang
Keyword(s):  
Feature Extraction ◽  
Time Scale ◽  
Recognition Rate ◽  
Support Vector ◽  
Svm Classifier ◽  
Feature Extraction Method ◽  
Radiated Noise ◽  
Intrinsic Time ◽  
Different Types ◽  
Time Scale Decomposition

To improve the feature extraction of ship-radiated noise in a complex ocean environment, fluctuation-based dispersion entropy is used to extract the features of ten types of ship-radiated noise. Since fluctuation-based dispersion entropy only analyzes the ship-radiated noise signal in single scale and it cannot distinguish different types of ship-radiated noise effectively, a new method of ship-radiated noise feature extraction is proposed based on fluctuation-based dispersion entropy (FDispEn) and intrinsic time-scale decomposition (ITD). Firstly, ten types of ship-radiated noise signals are decomposed into a series of proper rotation components (PRCs) by ITD, and the FDispEn of each PRC is calculated. Then, the correlation between each PRC and the original signal are calculated, and the FDispEn of each PRC is analyzed to select the Max-relative PRC fluctuation-based dispersion entropy as the feature parameter. Finally, by comparing the Max-relative PRC fluctuation-based dispersion entropy of a certain number of the above ten types of ship-radiated noise signals with FDispEn, it is discovered that the Max-relative PRC fluctuation-based dispersion entropy is at the same level for similar ship-radiated noise, but is distinct for different types of ship-radiated noise. The Max-relative PRC fluctuation-based dispersion entropy as the feature vector is sent into the support vector machine (SVM) classifier to classify and recognize ten types of ship-radiated noise. The experimental results demonstrate that the recognition rate of the proposed method reaches 95.8763%. Consequently, the proposed method can effectively achieve the classification of ship-radiated noise.

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