Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery

Tripathi, Manish Kumar; Nath, Abhigyan; Singh, T.P.; Ethayathulla, A.S.; Kaur, Punit

doi:10.1007/s11030-021-10256-w

Cited by 61 publications

(43 citation statements)

References 186 publications

(138 reference statements)

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“…The S1 subunit represents the variable part of the protein, while the S2 subunit is much more conserved. The first 13 amino acid residues constituting the signal peptide (SP) of S1 are required to guide its transportation to its membrane destination [22]. The S1 subunit contains the N-terminal domain (NTD) (14-305) and RBD spanning 319-541 residues.…”

Section: Structural Organization Of S Proteinmentioning

confidence: 99%

Structural and functional insights into the spike protein mutations of emerging SARS-CoV-2 variants

Gupta

Sharma

Singh

et al. 2021

Cell. Mol. Life Sci.

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Section: Structural Organization Of S Proteinmentioning

confidence: 99%

Structural and functional insights into the spike protein mutations of emerging SARS-CoV-2 variants

Gupta

Sharma

Singh

et al. 2021

Cell. Mol. Life Sci.

Self Cite

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“…Finally, the use of them can grasp the learning status of students, enhance students' experience, and help achieve personalized teaching. Through facial recognition technology, teachers can view students' expressions in time and learn about students' knowledge points through student expressions [ 33 ]. After receiving information of students' performance, the teacher can adjust the teaching plan and methods in time to realize personalized teaching.…”

Section: The Role Of Them In Promoting Online Music Teachingmentioning

confidence: 99%

Design of Online Music Education System Based on Artificial Intelligence and Multiuser Detection Algorithm

Hua

2022

Computational Intelligence and Neuroscience

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With the development of information technology, online music education has become a mainstream education method. Especially after the outbreak of COVID-19, music teachers have to teach through online. Therefore, an online music education system that can improve the quality of teaching is particularly important. Multiuser detection algorithms and artificial intelligence have important applications in many fields, and the field of music online education is no exception. This paper takes the music teaching of the music distance teaching unit as the goal and conducts sufficient research on the educational subjects such as teachers, students, and administrators. And with the help of the SCMA system multiuser detection algorithm and artificial intelligence technology, the system analysis and design method is used to analyze and design the music teaching function system. The system module involves basic information management, student music assignments, online courses, and other levels, providing an excellent educational system design example for music online education. The conclusion analysis shows that the music online education system based on SCMA system multiuser detection algorithm and artificial intelligence designed in this paper can significantly improve the audience’s music learning efficiency and has obvious benefits to the student group.

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“…A second experiment followed, in order to add more complexity and possibilities to the experiment, we added a different noise factor to the experiment in a noisy environment. And it was experimented with the previous fixed energy threshold method and two-stage detection method [18]. e results are given in Table 3.…”

Section: Test Of Embedded English Speech Recognition System Inmentioning

confidence: 99%

Automatic Error Detection Method of Embedded English Speech Teaching Recognition System under the Background of Artificial Intelligence

2022

Mobile Information Systems

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The embedded English speech teaching recognition system is a technology that writes the English speech recognition device control program into the chip and embeds the chip into the device, so that the human-like chip controls the English speech device to complete the speech recognition operation. Applying the embedded technology to the English speech recognition system can improve the recognition accuracy of the system to a higher level in terms of recognizing the English speech of a specific person. The purpose of this paper is to research and design an automatic error detection method for embedded English speech teaching recognition system in the context of artificial intelligence. This paper first gives a general introduction to the overview of artificial intelligence, then analyzes the speech recognition algorithm, uses MatLab software to obtain the correct number of recognition system words and the correct rate, and then implements the embedded English teaching recognition system in different environments. The experimental results of comparison through multiple test analysis show that in a quiet environment, the error rate of the embedded English speech teaching recognition system is very low, and the correct recognition rate can reach more than 90%. In a noisy environment affected by various noises, the correct recognition rate of the embedded English speech teaching recognition system is basically above 60%.

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Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery

Cited by 61 publications

References 186 publications

Structural and functional insights into the spike protein mutations of emerging SARS-CoV-2 variants

Structural and functional insights into the spike protein mutations of emerging SARS-CoV-2 variants

Design of Online Music Education System Based on Artificial Intelligence and Multiuser Detection Algorithm

Automatic Error Detection Method of Embedded English Speech Teaching Recognition System under the Background of Artificial Intelligence

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