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Institution

Jaypee Institute of Information Technology

EducationNoida, Uttar Pradesh, India
About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.


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Journal ArticleDOI
23 Feb 2021
TL;DR: In this article, the authors focused on understanding population-specific variations attributed to SARS-CoV-2 infections in specific geographical regions particularly in the United States and found that only 67.46% of single nucleotide polymorphism (SNP) mutations were at the amino acid level.
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in 92 million cases in a span of 1 year. The study focuses on understanding population-specific variations attributing its high rate of infections in specific geographical regions particularly in the United States. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d, and e (subtypes e1 and e2). Clade d and subclade e2 were found exclusively comprised of U.S. strains. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2, and Nsp6. Our analysis revealed that only 67.46% of single nucleotide polymorphism (SNP) mutations were at the amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except for 6 strains which were marked as ancestral type, whereas co-mutation (P409L and Y446C) in Nsp13 were found in 64 genomes from the United States highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of spike proteins with angiotensin-converting enzyme 2 (ACE2), but it also showed better interaction with the TMPRSS2 receptor contributing to high transmissibility among U.S. strains. We also found host proteins, MYO5A, MYO5B, and MYO5C, that had maximum interaction with viral proteins (nucleocapsid [N], spike [S], and membrane [M] proteins). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for coronavirus disease 2019 (COVID-19) treatment. The functional annotations of the host-pathogen interaction (HPI) network were found to be closely associated with hypoxia and thrombotic conditions, confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 and N conferring the ability of SARS-CoV-2 to enter and trigger zinc antiviral protein (ZAP) activity inside the host cell.IMPORTANCE In the current study, we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions especially in U.S. strains. Compositional structural biology results suggested that mutations have a balance of opposing forces affecting pathogenicity suggesting that only a few mutations are effective at the translation level. Novel HPI analysis and CpG predictions elucidate the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population-specific variations attributing a high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies.

14 citations

Journal ArticleDOI
TL;DR: In this article, the authors used Plackett-Burman design to optimize the Bioprocess variables (pH, relative humidity (RH), nitrogen source (gram flour) and incubation time) for laccase production.

14 citations

Journal ArticleDOI
TL;DR: In this paper, the conduction and valence band offsets of Zn1−x Sb x O/ZnO based quantum well devices were measured by photo-electron spectroscopy and consequently, the voltage-sensitive conduction band offset was calculated by UV-visible spectrographs.
Abstract: Accurate knowledge of the alignment of conduction and valence bands of layers at the heterojunction and warrant knowledge of the band offsets at the interface is essential for Zn1−x Sb x O/ZnO based quantum well device designing and modeling. Under this scenario, valence band offsets of Zn1−x Sb x O/ZnO heterostructures grown by the pulsed laser deposition technique was measured by photoelectron spectroscopy and consequently, the conduction band offset was calculated by UV-visible spectroscopy. The change in band alignment has been observed with the dopant (Sb) concentration. Ratios of conduction band offset to valence band offset were estimated to be 1.67 and 0.04 for x = 0.03 and 0.06, respectively, for Sb doped films. A Type-II band alignment was observed at the Zn0.97Sb0.03O/ZnO interface, whereas the Type-I band alignment took place at the Zn0.94Sb0.06O/ZnO interface.

14 citations

Proceedings ArticleDOI
04 Apr 2015
TL;DR: A statistical channel model called as log-normal distribution is presented to describe the irradiance fluctuations in weak turbulence for FSO communication systems and investigates performance of the direct detection FSO system over the log- normal turbulence channel.
Abstract: Free space optical (FSO) propagation over atmospheric turbulence affected by fluctuations in both intensity as well as in phase of received signal This result decreases electrical signal to noise ratio (SNR) and because of this degradation it impaired performance In this paper, we are discuss a comparative analysis of bit error rate (BER) performance for the on-off keying (OOK) modulated direct detection and coherent detection FSO communication systems in weak turbulence conditions We present a statistical channel model called as log-normal distribution to describe the irradiance fluctuations in weak turbulence for FSO communication systems First, we investigate performance of the direct detection FSO system over the log-normal turbulence channel and derived the closed form expression for BER in term of average received irradiance and SNR, and then we do same for coherent detection FSO system, finally, compare both of them

14 citations

Journal ArticleDOI
TL;DR: A new Grey relational analysis-based bag- of-features method which improves the efficiency of vector quantization step of the standard bag-of- Features method and is validated in terms of precision, recall, G-mean, F1 score, and radar charts.
Abstract: With the expeditious development of current medical imaging technology, the availability of histopathological images has been increased in a large number. Hence, histopathological image classification and annotation have emerged as the prime research fields in the pathological diagnosis and clinical practices. Several methods are available for the automation of image classification. Recently, the bag-of-features appeared as a successful histopathological image classification method. However, all the extracted keypoints in bag-of-features are not relevant and generally have very high dimensions, which degrade the performance of a classifier. Therefore, this paper introduces a new Grey relational analysis-based bag-of-features method to search the relevant keypoints. The efficacy of the proposed method has been analyzed on animal diagnostics lab histopathological image datasets having healthy and inflamed images of three organs. The average accuracy of the proposed method is 88.3%, which is the highest among other state-of-the-art methods. This paper introduced a new Grey relational analysis-based bag-of-features which improves the efficiency of vector quantization step of the standard bag-of-features method. The method used Grey relational analysis for similarity measure in vector quantization method of bag-offeatures. The proposed method has been validated in terms of precision, recall, G-mean, F1 score, and radar charts on three datasets, Kidney, Lung, and Spleen of ADL histopathological images.

14 citations


Authors

Showing all 2176 results

NameH-indexPapersCitations
Sanjay Gupta9990235039
Mohsen Guizani79111031282
José M. Merigó5536110658
Ashish Goel502059941
Avinash C. Pandey453017576
Krishan Kumar352424059
Yogendra Kumar Gupta351834571
Nidhi Gupta352664786
Anirban Pathak332143508
Amanpreet Kaur323675713
Navneet Sharma312193069
Garima Sharma31973348
Manoj Kumar301082660
Rahul Sharma301893298
Ghanshyam Singh292632957
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202321
202258
2021401
2020395
2019464
2018366