Investigation of the binding affinity of C-terminal domain of SARS coronavirus nucleocapsid protein to nucleotide using AlGaN/GaN high electron mobility transistors

Hsu, You-Ren; Lee, Geng-Yen; Chyi, Jen‐Inn; Chang, Chung-ke; Huang, Chih-Cheng; Hsu, Chen-Pin; Huang, Tai-huang; Ren, F.; Wang, Yulin

doi:10.1109/icsens.2012.6411277

Cited by 4 publications

(5 citation statements)

References 16 publications

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“…The SARS-CoV-2 virus affects the central nervous system and creates risk for the life of Alzheimer's disease patients [16,17]. The LSPCF biosensor is used to detect the coronavirus [18]. The authors applied AlGaN/GaN HEMTs to detect the protein in the coronavirus [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of COVID-19 and its Impact on Alzheimer’s Patient using Machine Learning Techniques

Sivakani¹,

Masood²

2022

IJC

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In this world, there is fast growth in technology, as technology growth is there the human also move fast based on the growth in technology. New diseases also growing fast in the world. In this paper, a semi-supervised approach has been proposed for the classification of the COVID-19 and a study has been done to analyze the impact of the covid on Alzheimer’s disease patients. Coronavirus disease is a respiratory infection disease and Alzheimer’s disease is a brain disease. From the literature, it has been analyzed that, because of the coronavirus the immunity system will be affected in humans and there is a chance to affect the brain also. Classification and clustering have been done on the coronavirus dataset and validated using a 10-fold validation process. The classifiers applied are Naïve Bayes and Random Forest; the results obtained are 99.88% and 100% accuracy. Also, the clustering has been applied and 2 clusters are generated for grouping the classes. Then a study has been done for predicting the impact of the coronavirus on Alzheimer’s patients.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of COVID-19 and its Impact on Alzheimer’s Patient using Machine Learning Techniques

Sivakani¹,

Masood²

2022

IJC

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“…Accurate and selective assessment of SARS-CoV would assist in the effective diagnosis of infected individual, offer clinical guidance and aid in assessing clinical outcomes (see Table 1 ). Until now, specific 41-base SARS-CoV double-stranded DNA (dsDNA) genome, single biotinylated deoxyribonucleic acid (DNA)/streptavidin-coated sensor chip, S protein/human angiotensin-converting enzyme 2, SARS-CoV specific antibody/protein A and Feline coronavirus (FIP) type I anti-viral antiserum were the reported bio-recognition elements widely used to detect SARS-CoV [70] , [71] , [72] , [73] , [74] .…”

Section: Sars-covmentioning

confidence: 99%

“…To improve the binding affinity between SARS-CoV dsDNA genome and C-terminal domain of SARS-CoV nucleocapsid protein, Hsu et al [74] utilized high electron mobility transistors fabricated with two different materials including aluminium gallium nitride and gallium nitride. Hsu et al [74] correlated the binding affinity between SARS-CoV dsDNA genome and C-terminal domain of SARS-CoV nucleocapsid protein with disassociation constant for the quantitative SARS-CoV detection. Hsu et al [74] observed that there were at least two binding sites on the SARS-CoV dsDNA genome, which facilitate the binding of nucleotide – protein interaction.…”

Section: Sars-covmentioning

confidence: 99%

“…Hsu et al [74] correlated the binding affinity between SARS-CoV dsDNA genome and C-terminal domain of SARS-CoV nucleocapsid protein with disassociation constant for the quantitative SARS-CoV detection. Hsu et al [74] observed that there were at least two binding sites on the SARS-CoV dsDNA genome, which facilitate the binding of nucleotide – protein interaction. Their corresponding disassociation constants were estimated as 0.052 nM and 51.24 nM.…”

Section: Sars-covmentioning

confidence: 99%

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SARS-CoV, MERS-CoV and SARS-CoV-2: A Diagnostic Challenge

2021

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Highlights The highly pathogenic MERS-CoV, SARS-CoV and SARS-CoV-2 cause acute illness and are often fatal. MERS-CoV, SARS-CoV and SARS-CoV-2 tend to infect the respiratory tract and can cause acute respiratory syndrome. SARS-related mortality rate is relatively higher than influenza. CT scans and RT-PCR are the most promising diagnostic tools for COVID-19 diagnosis.

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“…AlGaN/GaN HEMT, one of the representative structured transistors in the third-generation semiconductor technology, provides many advantageous properties over silicon technology, such as a large critical electric field, high electron mobility, high saturation current, and an excellent temperature capability [1][2][3][4], due to its wide band gap and twodimension electron gas (2DEG) density. Such outstanding performance makes the HEMT device a highly anticipated candidate in future high-power and high-frequency applications [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Contact Resistance and DC Characteristics for AlGaN/GaN HEMTs Utilizing Sub-10 nm Nanohole Etching

Lee,

Pan

et al. 2024

Electronics

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In this paper, the contact resistance of AlGaN/GaN high electron mobility transistor (HEMT) was improved by introducing nanoscale hole arrays in ohmic regions, and the DC characteristics of the conventional structure and nanohole etching structure for HEMTs were measured for comparison. Sub-10 nm nanoholes were patterned on the ohmic area surface of AlGaN using electron beam lithography and a low-temperature short-time development. Various dwell times of e-beam exposure from 5 to 30 μs were investigated and the corresponding contact resistance of the nano hole etching structure and planar structure were compared by the transmission line model (TLM) method. We observed a reduced contact resistance from 1.82 to 0.47 Ω-mm by performing a dwell time of 5 μs of exposure for nanohole formation compared to the conventional structure. Furthermore, the DC characteristics demonstrate that the maximum drain current for HEMTs was enhanced from 319 to 496 mA/mm by utilizing this optimized ohmic contact. These results show that devices with sub-10 nm nanohole ohmic contacts exhibit an improved contact resistance over the conventional structure, optimizing device performance for HEMTs, including a lower on-resistance and higher maximum drain current.

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Investigation of the binding affinity of C-terminal domain of SARS coronavirus nucleocapsid protein to nucleotide using AlGaN/GaN high electron mobility transistors

Cited by 4 publications

References 16 publications

Analysis of COVID-19 and its Impact on Alzheimer’s Patient using Machine Learning Techniques

Analysis of COVID-19 and its Impact on Alzheimer’s Patient using Machine Learning Techniques

SARS-CoV, MERS-CoV and SARS-CoV-2: A Diagnostic Challenge

Optimization of Contact Resistance and DC Characteristics for AlGaN/GaN HEMTs Utilizing Sub-10 nm Nanohole Etching

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