Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples.
Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples.
Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples.
This work presents a novel knowledge‐based approach that uses state‐of‐the‐art convolutional neural networks, where the algorithm is learned by examples, ...
Mar 19, 2020 · Unlike P2RANK however, DeepSite uses a deep 3D convolutional neural network, with an architecture typical for image classification problems – ...
In this work, we propose a novel workflow for predicting possible binding sites of a ligand on a protein surface.
Oct 22, 2024 · The algorithm predicts potential binding sites by determining atomic contacts between the PDB chains, dinucleotide patterns of the RNA, and ( ...
Sep 8, 2021 · In this study, we present a deep learning model PUResNet and a novel data cleaning process based on structural similarity for predicting protein-ligand binding ...
DeepSite: protein-binding site predictor using 3D-convolutional neural networks ... using protein-language-model-informed equivariant deep graph neural networks.
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Jun 12, 2024 · Nikam et al. (2023) established the deep neural network DeepBSRPred to predict protein binding sites based on specific sequence and structural ...