Our multi-level combination pipeline (Fig. 1) for protein structure prediction is generally comprised of five steps: (i) template identification and ranking, (ii) multi-template combination, (iii) model generation, (iv) model evaluation and (v) model combination and refinement.
Abstract: Proposes novel prediction schemes for protein 3D structure prediction that include both local and global factors of protein structure formation.
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Multi-domain and complex protein structure prediction using inter ...
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Dec 1, 2023 · DeepAssembly is designed to automatically construct multi-domain protein or complex structure through inter-domain interactions from deep learning.
We propose a novel scheme for protein 3D structure prediction using the Multi-level Description scheme (MLD). In this prediction scheme, a local conformation is ...
Apr 1, 2010 · Here we describe MULTICOM, a multi-level combination approach to improve the various steps in protein structure prediction.
Sep 15, 2021 · We present a deep learning framework for multi-level peptide-protein interaction prediction, called CAMP, including binary peptide-protein interaction ...
The traditional paradigm of protein structure prediction generally consists of two phases: 1) candidate model generation and 2) model selection. For many ...
Feb 27, 2024 · To address this issue, we introduce a span mask pre-training strategy on 3D protein chains to learn meaningful representations of both residues ...
Feb 1, 2023 · Most existing function prediction methods take the tertiary structure as input, unintentionally ignoring the other levels of protein structures.
This study introduces a novel and efficient method for determining the PSSP domain, which is poised to deepen our understanding of the practical applications ...