AIMC Topic: Sequence Analysis, Protein

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Multi-Scale Capsule Network for Predicting DNA-Protein Binding Sites.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Discovering DNA-protein binding sites, also known as motif discovery, is the foundation for further analysis of transcription factors (TFs). Deep learning algorithms such as convolutional neural networks (CNN) have been introduced to motif discovery ...
Algorithms Deep Learning Sequence Analysis, Protein Chromatin Immunoprecipitation Sequencing Transcription Factors DNA-Binding Proteins Binding Sites Protein Binding Computational Biology
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AIEpred: An Ensemble Predictive Model of Classifier Chain to Identify Anti-Inflammatory Peptides.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Anti-inflammatory peptides (AIEs) have recently emerged as promising therapeutic agent for treatment of various inflammatory diseases, such as rheumatoid arthritis and Alzheimer's disease. Therefore, detecting the correlation between amino acid seque...
Amino Acid Sequence Sequence Analysis, Protein Machine Learning Computational Biology Algorithms Models, Statistical Peptides Anti-Inflammatory Agents Drug Discovery
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Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Protein fold recognition is one of the most essential steps for protein structure prediction, aiming to classify proteins into known protein folds. There are two main computational approaches: one is the template-based method based on the alignment s...
Algorithms Pattern Recognition, Automated Protein Folding Sequence Analysis, Protein Computational Biology Support Vector Machine Proteins
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When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14-(tFold for CASP14 contact prediction).

Proteins Sep 23, 2021
In this paper, we report our tFold framework's performance on the inter-residue contact prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our tFold framework seamlessly combines both homologous sequences and st...
Reproducibility of Results Computational Biology Proteins Neural Networks, Computer Software Structural Homology, Protein Models, Molecular Protein Folding Sequence Analysis, Protein
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PARROT is a flexible recurrent neural network framework for analysis of large protein datasets.

eLife Sep 17, 2021
The rise of high-throughput experiments has transformed how scientists approach biological questions. The ubiquity of large-scale assays that can test thousands of samples in a day has necessitated the development of new computational approaches to i...
Computational Biology Proteins Databases, Protein Phosphorylation High-Throughput Nucleotide Sequencing Sequence Analysis, Protein Neural Networks, Computer Software Deep Learning Humans
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Protein inter-residue contact and distance prediction by coupling complementary coevolution features with deep residual networks in CASP14.

Proteins Aug 19, 2021
This article reports and analyzes the results of protein contact and distance prediction by our methods in the 14th Critical Assessment of techniques for protein Structure Prediction (CASP14). A new deep learning-based contact/distance predictor was ...
Software Protein Conformation Deep Learning Computational Biology Sequence Alignment Proteins Sequence Analysis, Protein Models, Molecular
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Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.

Proteins Aug 17, 2021
The trRosetta structure prediction method employs deep learning to generate predicted residue-residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs (in addition to se...
Humans Software Deep Learning Computational Biology Proteins Protein Structure, Tertiary Sequence Analysis, Protein Metagenome
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PYTHIA: Deep Learning Approach for Local Protein Conformation Prediction.

International journal of molecular sciences Aug 17, 2021
Protein Blocks (PBs) are a widely used structural alphabet describing local protein backbone conformation in terms of 16 possible conformational states, adopted by five consecutive amino acids. The representation of complex protein 3D structures as 1...
Deep Learning Humans Proteins Databases, Protein Neural Networks, Computer Software Models, Molecular Algorithms Protein Conformation Sequence Analysis, Protein
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Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14.

Proteins Aug 7, 2021
In this article, we report 3D structure prediction results by two of our best server groups ("Zhang-Server" and "QUARK") in CASP14. These two servers were built based on the D-I-TASSER and D-QUARK algorithms, which integrated four newly developed com...
Sequence Analysis, Protein Proteins Models, Molecular Software Hydrogen Bonding Deep Learning Protein Conformation Protein Folding Computational Biology Sequence Alignment
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Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14.

Proteins Jul 27, 2021
Substantial progresses in protein structure prediction have been made by utilizing deep-learning and residue-residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system by inc...
Algorithms Humans Deep Learning Software Proteins Sequence Analysis, Protein Models, Molecular Sequence Alignment Protein Structure, Tertiary
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