Transformer architecture and attention mechanisms in genome data analysis: a comprehensive review
SR Choi, M Lee - Biology, 2023 - mdpi.com
Simple Summary The rapidly advancing field of deep learning, specifically transformer-
based architectures and attention mechanisms, has found substantial applicability in …
based architectures and attention mechanisms, has found substantial applicability in …
Nucleic acid degradation as barrier to gene delivery: a guide to understand and overcome nuclease activity
Gene therapy is on its way to revolutionize the treatment of both inherited and acquired
diseases, by transferring nucleic acids to correct a disease-causing gene in the target cells …
diseases, by transferring nucleic acids to correct a disease-causing gene in the target cells …
Cyberbullying detection on twitter using deep learning-based attention mechanisms and continuous Bag of words feature extraction
Since social media platforms are widely used and popular, they have given us more
opportunities than we can even imagine. Despite all of the known benefits, some users may …
opportunities than we can even imagine. Despite all of the known benefits, some users may …
Cyberbullying detection on social media using stacking ensemble learning and enhanced BERT
The prevalence of cyberbullying on Social Media (SM) platforms has become a significant
concern for individuals, organizations, and society as a whole. The early detection and …
concern for individuals, organizations, and society as a whole. The early detection and …
Data-driven analytics leveraging artificial intelligence in the era of COVID-19: an insightful review of recent developments
A Majeed, SO Hwang - Symmetry, 2021 - mdpi.com
This paper presents the role of artificial intelligence (AI) and other latest technologies that
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …
Comparative study of lipid nanoparticle-based mRNA vaccine bioprocess with machine learning and combinatorial artificial neural network-design of experiment …
To develop a combinatorial artificial-neural-network design-of-experiment (ANN-DOE)
model, the effect of ionizable lipid, an ionizable lipid-to-cholesterol ratio, N/P ratio, flow rate …
model, the effect of ionizable lipid, an ionizable lipid-to-cholesterol ratio, N/P ratio, flow rate …
Covid vaccine adverse side-effects prediction with sequence-to-sequence model
S Zacharia, A Kodipalli - … and applications: proceedings of ERCICA 2022, 2022 - Springer
COVID-19 caused more than 5 million deaths in the world. After lot of efforts and hard work
of many scientists, few vaccines are discovered and are approved for use. It is necessary to …
of many scientists, few vaccines are discovered and are approved for use. It is necessary to …
An agent-based transmission model of COVID-19 for re-opening policy design
The global pandemic caused by the coronavirus (COVID-19) disease has collapsed the
worldwide economy. Elements such as non-obligatory vaccination, new strain variants and …
worldwide economy. Elements such as non-obligatory vaccination, new strain variants and …
[PDF][PDF] Short term residential load forecasting using long short-term memory recurrent neural network.
Load forecasting plays an essential role in power system planning. The efficiency and
reliability of the whole power system can be increased with proper planning and …
reliability of the whole power system can be increased with proper planning and …
[HTML][HTML] mRNA vaccine sequence and structure design and optimization: Advances and challenges
L Jin, Y Zhou, S Zhang, SJ Chen - Journal of Biological Chemistry, 2024 - Elsevier
Messenger RNA (mRNA) vaccines have emerged as a powerful tool against communicable
diseases and cancers, as demonstrated by their huge success during the coronavirus …
diseases and cancers, as demonstrated by their huge success during the coronavirus …