Quantum computing in bioinformatics: a systematic review map**
K Nałęcz-Charkiewicz, K Charkiewicz… - Briefings in …, 2024 - academic.oup.com
The field of quantum computing (QC) is expanding, with efforts being made to apply it to
areas previously covered by classical algorithms and methods. Bioinformatics is one such …
areas previously covered by classical algorithms and methods. Bioinformatics is one such …
Alphadesign: A graph protein design method and benchmark on alphafolddb
While DeepMind has tentatively solved protein folding, its inverse problem--protein design
which predicts protein sequences from their 3D structures--still faces significant challenges …
which predicts protein sequences from their 3D structures--still faces significant challenges …
Cost-effective fault diagnosis of nearby photovoltaic systems using graph neural networks
The energy losses and costs associated with faults in photovoltaic (PV) systems significantly
limit the efficiency and reliability of solar power. Since existing methods for automatic fault …
limit the efficiency and reliability of solar power. Since existing methods for automatic fault …
KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement
Recent studies have shown competitive performance in protein inverse folding, while most
of them disregard the importance of predictive confidence, fail to cover the vast protein …
of them disregard the importance of predictive confidence, fail to cover the vast protein …
Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment
Security-constrained unit commitment (SCUC) is a computationally complex process utilized
in power system day-ahead scheduling and market clearing. SCUC is run daily and requires …
in power system day-ahead scheduling and market clearing. SCUC is run daily and requires …
Reduced optimal power flow using graph neural network
OPF problems are formulated and solved for power system operations, especially for
determining generation dispatch points in real-time. For large and complex power system …
determining generation dispatch points in real-time. For large and complex power system …
Algorithms for protein design
S Talluri - Advances in Protein Chemistry and Structural Biology, 2022 - Elsevier
Abstract Computational Protein Design has the potential to contribute to major advances in
enzyme technology, vaccine design, receptor-ligand engineering, biomaterials …
enzyme technology, vaccine design, receptor-ligand engineering, biomaterials …
Inferring the interaction rules of complex systems with graph neural networks and approximate Bayesian computation
J Gaskell, N Campioni, JM Morales… - Journal of the …, 2023 - royalsocietypublishing.org
Inferring the underlying processes that drive collective behaviour in biological and social
systems is a significant statistical and computational challenge. While simulation models …
systems is a significant statistical and computational challenge. While simulation models …
Resource analysis of quantum algorithms for coarse-grained protein folding models
Protein folding processes are a vital aspect of molecular biology that is hard to simulate with
conventional computers. Quantum algorithms have been proven superior for certain …
conventional computers. Quantum algorithms have been proven superior for certain …
Graph Neural Network-Accelerated Network-Reconfigured Optimal Power Flow
T Pham, X Li - arxiv preprint arxiv:2410.17460, 2024 - arxiv.org
Optimal power flow (OPF) has been used for real-time grid operations. Prior efforts
demonstrated that utilizing flexibility from dynamic topologies will improve grid efficiency …
demonstrated that utilizing flexibility from dynamic topologies will improve grid efficiency …