[HTML][HTML] iVaccine-Deep: Prediction of COVID-19 mRNA vaccine degradation using deep learning
Messenger RNA (mRNA) has emerged as a critical global technology that requires global
joint efforts from different entities to develop a COVID-19 vaccine. However, the chemical …
joint efforts from different entities to develop a COVID-19 vaccine. However, the chemical …
Deep learning for automated classification and characterization of amorphous materials
It is difficult to quantify structure–property relationships and to identify structural features of
complex materials. The characterization of amorphous materials is especially challenging …
complex materials. The characterization of amorphous materials is especially challenging …
Scalable Inhibitors of the Nsp3–Nsp4 Coupling in SARS-CoV-2
The human Betacoronavirus SARS-CoV-2 is a novel pathogen claiming millions of lives and
causing a global pandemic that has disrupted international healthcare systems, economies …
causing a global pandemic that has disrupted international healthcare systems, economies …
A deep graph network–enhanced sampling approach to efficiently explore the space of reduced representations of proteins
The limits of molecular dynamics (MD) simulations of macromolecules are steadily pushed
forward by the relentless development of computer architectures and algorithms. The …
forward by the relentless development of computer architectures and algorithms. The …
Geometric learning of knot topology
Knots are deeply entangled with every branch of science. One of the biggest open
challenges in knot theory is to formalise a knot invariant that can unambiguously and …
challenges in knot theory is to formalise a knot invariant that can unambiguously and …
Deep learning model with ensemble techniques to compute the secondary structure of proteins
Protein secondary structure is the local conformation assigned to protein sequences with the
help of its three-dimensional structure. Assigning the local conformation to protein …
help of its three-dimensional structure. Assigning the local conformation to protein …
Autoencoder-assisted study of directed percolation with spatial long-range interactions
Y Wang, Y Yang, W Li - arXiv preprint arXiv:2311.12426, 2023 - arxiv.org
Spatial L {\'{e}} vy-like flights are introduced as a way to absorbing phase transitions to
produce non-local interactions. We utilize the autoencoder, an unsupervised learning …
produce non-local interactions. We utilize the autoencoder, an unsupervised learning …
Artificial neural network (ANN) techniques in solving the protein folding problem
R Satpathy - Advanced AI Techniques and Applications in …, 2021 - taylorfrancis.com
Proteins are one of the essential bio-molecules and control almost all functions in the living
cell. They act to perform many of the biological functions in different forms, including catalytic …
cell. They act to perform many of the biological functions in different forms, including catalytic …
Accelerating the identification of informative reduced representations of proteins with deep learning for graphs
The limits of molecular dynamics (MD) simulations of macromolecules are steadily pushed
forward by the relentless developments of computer architectures and algorithms. This …
forward by the relentless developments of computer architectures and algorithms. This …
[PDF][PDF] Computer and Information Sciences
abstract Messenger RNA (mRNA) has emerged as a critical global technology that requires
global joint efforts from different entities to develop a COVID-19 vaccine. However, the …
global joint efforts from different entities to develop a COVID-19 vaccine. However, the …