Search alternatives:
protein optimization » process optimization (Expand Search), property optimization (Expand Search), driven optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
library based » laboratory based (Expand Search)
based protein » capsid protein (Expand Search), based proteomics (Expand Search)
binary wave » binary image (Expand Search)
wave model » naive model (Expand Search), game model (Expand Search), base model (Expand Search)
protein optimization » process optimization (Expand Search), property optimization (Expand Search), driven optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
library based » laboratory based (Expand Search)
based protein » capsid protein (Expand Search), based proteomics (Expand Search)
binary wave » binary image (Expand Search)
wave model » naive model (Expand Search), game model (Expand Search), base model (Expand Search)
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RosettaAMRLD: A Reaction-Driven Approach for Structure-Based Drug Design from Combinatorial Libraries with Monte Carlo Metropolis Algorithms
Published 2025“…By leveraging combinatorial ultralarge libraries, RosettaAMRLD ensures synthetic accessibility, optimizing protein–ligand interactions while efficiently sampling accessible chemical space. …”
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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
Published 2024“…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …”
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Optimal 8-mer and 9-mer SARS-CoV-2 epitope identification.
Published 2020“…Peptide sequences are named based on the protein they are contained within, followed by the number of the first amino acid residue of the peptide in the context of the full protein, to the last amino acid residue. potential optimal 8-mer or 9-mer CD8+ T cell epitopes were predicted. …”
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MCLP_quantum_annealer_V0.5
Published 2025“…Theoretical and applied experiments are conducted using four solvers: QBSolv, D-Wave Hybrid binary quadratic model 2, D-Wave Advantage system 4.1, and Gurobi. …”
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Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential
Published 2023“…This information is useful to guide the construction of libraries for shape-based virtual screening and to improve the docking algorithm to efficiently sample bound conformations.…”
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Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential
Published 2023“…This information is useful to guide the construction of libraries for shape-based virtual screening and to improve the docking algorithm to efficiently sample bound conformations.…”
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DataSheet1_Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: an in vitro study.docx
Published 2024“…</p><p>Methods: We developed Quantum-assisted Fragment-based Automated Structure Generator (QFASG), a fully automated algorithm designed to construct ligands for a target protein using a library of molecular fragments. …”
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