AIMC Topic: Sequence Alignment

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Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2023
The encounter of large amounts of biological sequence data generated during the last decades and the algorithmic and hardware improvements have offered the possibility to apply machine learning techniques in bioinformatics. While the machine learning...
Mathematics Sequence Alignment Sequence Analysis Machine Learning Algorithms
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Single-sequence protein structure prediction using a language model and deep learning.

Nature biotechnology Oct 3, 2022
AlphaFold2 and related computational systems predict protein structure using deep learning and co-evolutionary relationships encoded in multiple sequence alignments (MSAs). Despite high prediction accuracy achieved by these systems, challenges remain...
Protein Conformation Sequence Alignment Computational Biology Proteins Language Deep Learning
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Sequence-based drug-target affinity prediction using weighted graph neural networks.

BMC genomics Jun 17, 2022
BACKGROUND: Affinity prediction between molecule and protein is an important step of virtual screening, which is usually called drug-target affinity (DTA) prediction. Its accuracy directly influences the progress of drug development. Sequence-based d...
Proteins Amino Acid Sequence Sequence Alignment Neural Networks, Computer Drug Development
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Neural Network and Random Forest Models in Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Jun 3, 2022
Over the past decade, the demand for automated protein function prediction has increased due to the volume of newly sequenced proteins. In this paper, we address the function prediction task by developing an ensemble system automatically assigning Ge...
Neural Networks, Computer Software Proteins Databases, Protein Sequence Alignment
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AF2Complex predicts direct physical interactions in multimeric proteins with deep learning.

Nature communications Apr 1, 2022
Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the sam...
Deep Learning Proteome Neural Networks, Computer Escherichia coli Sequence Alignment
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EvoRator: Prediction of Residue-level Evolutionary Rates from Protein Structures Using Machine Learning.

Journal of molecular biology Mar 11, 2022
Measuring evolutionary rates at the residue level is indispensable for gaining structural and functional insights into proteins. State-of-the-art tools for estimating rates take as input a large set of homologous proteins, a probabilistic model of ev...
Internet Use Phylogeny Proteins Protein Conformation Sequence Alignment Software Algorithms Humans Machine Learning
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Boltzmann Machine Learning and Regularization Methods for Inferring Evolutionary Fields and Couplings From a Multiple Sequence Alignment.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
The inverse Potts problem to infer a Boltzmann distribution for homologous protein sequences from their single-site and pairwise amino acid frequencies recently attracts a great deal of attention in the studies of protein structure and evolution. We ...
Machine Learning Amino Acid Sequence Proteins Sequence Alignment
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ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs.

Journal of computational biology : a journal of computational molecular cell biology Jan 21, 2022
Template-based modeling (TBM), including homology modeling and protein threading, is one of the most reliable techniques for protein structure prediction. It predicts protein structure by building an alignment between the query sequence under predict...
Algorithms Deep Learning Proteins Models, Molecular Computational Biology Neural Networks, Computer Sequence Analysis, Protein Sequence Alignment Amino Acid Motifs Amino Acid Sequence Software Protein Conformation
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Protein Fold Recognition Based on Auto-Weighted Multi-View Graph Embedding Learning Model.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Protein fold recognition is critical for studies of the protein structure prediction and drug design. Several methods have been proposed to obtain discriminative features from the protein sequences for fold recognition. However, the ensemble methods ...
Machine Learning Algorithms Sequence Alignment Sequence Analysis, Protein Computational Biology Proteins Databases, Protein Amino Acid Sequence Protein Folding
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Evaluation of Deep Neural Network ProSPr for Accurate Protein Distance Predictions on CASP14 Targets.

International journal of molecular sciences Nov 27, 2021
The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference ...
Software Design Protein Structural Elements Amino Acid Sequence Computational Biology Protein Folding Humans Protein Conformation Proteins Neural Networks, Computer Sequence Alignment
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