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Drug Design

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Showing 326–350 of 440 papers

TitleStatusHype
Two for the Price of One: Integrating Large Language Models to Learn Biophysical Interactions—0
Understanding of Genetic Code Degeneracy and New Way of Classifying of Protein Family: A Mathematical Approach—0
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models—0
Unified Guidance for Geometry-Conditioned Molecular Generation—0
Synergistic Benefits of Joint Molecule Generation and Property Prediction—0
Uni-Mol: A Universal 3D Molecular Representation Learning Framework—0
Unveiling the frontiers of deep learning: innovations shaping diverse domains—0
Using Deep Reinforcement Learning to Generate Rationales for Molecules—0
Using the structural kinome to systematize kinase drug discovery—0
Vertex-Edge Weighted Molecular Graphs: A study on topological indices and their relevance to physicochemical properties of drugs in use cancer treatment—0
Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification—0
Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model—0
xTrimoABFold: De novo Antibody Structure Prediction without MSA—0
Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development—0
New Candidates for Furin Inhibition as Probable Treat for COVID-19: Docking Output—0
NLRP3 monomer Functional Dynamics: from the Effects of Allosteric Binding to Implications for Drug Design—0
Old Drugs for Newly Emerging Viral Disease, COVID-19: Bioinformatic Prospective—0
One-way Explainability Isn't The Message—0
Optimization of Tree Ensembles—0
Optimized Drug Design using Multi-Objective Evolutionary Algorithms with SELFIES—0
Optimizing Drug Design by Merging Generative AI With Active Learning Frameworks—0
Overview of Current Type I/II Kinase Inhibitors—0
ParaVS: A Simple, Fast, Efficient and Flexible Graph Neural Network Framework for Structure-Based Virtual Screening—0
PepINVENT: Generative peptide design beyond the natural amino acids—0
Persistent Dirac for molecular representation—0
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