AIMC Topic: Sequence Alignment

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Protein structure search to support the development of protein structure prediction methods.

Proteins Feb 2, 2021
Protein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction metho...
Humans Research Design Deep Learning Amino Acid Motifs Structural Homology, Protein Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Proteins Benchmarking Sequence Alignment
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Classifying the superfamily of small heat shock proteins by using g-gap dipeptide compositions.

International journal of biological macromolecules Nov 17, 2020
Small heat shock protein (sHSP) is a superfamily of molecular chaperone and is found from archaea to human. Recent researches have demonstrated that sHSPs participate in a series of biological processes and are even closely associated with serious di...
Databases, Protein Amino Acid Sequence Dipeptides Animals Computational Biology Proteomics Sequence Alignment Humans Heat-Shock Proteins, Small Machine Learning
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ReFold-MAP: Protein remote homology detection and fold recognition based on features extracted from profiles.

Analytical biochemistry Nov 6, 2020
Protein remote homology detection and protein fold recognition are two important tasks in protein structure and function prediction. There are three kinds of methods in this field, including the discriminative methods, the alignment methods, and the ...
Sequence Analysis, Protein Artificial Intelligence Databases, Protein Proteins Protein Folding Sequence Alignment
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DNSS2: Improved ab initio protein secondary structure prediction using advanced deep learning architectures.

Proteins Sep 16, 2020
Accurate prediction of protein secondary structure (alpha-helix, beta-strand and coil) is a crucial step for protein inter-residue contact prediction and ab initio tertiary structure prediction. In a previous study, we developed a deep belief network...
Neural Networks, Computer Software Deep Learning Markov Chains Sequence Alignment Sequence Homology, Amino Acid Protein Conformation, alpha-Helical Proteins Databases, Protein Amino Acid Sequence Protein Conformation, beta-Strand
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Use of Chou's 5-steps rule to predict the subcellular localization of gram-negative and gram-positive bacterial proteins by multi-label learning based on gene ontology annotation and profile alignment.

Journal of integrative bioinformatics Jun 29, 2020
To date, many proteins generated by large-scale genome sequencing projects are still uncharacterized and subject to intensive investigations by both experimental and computational means. Knowledge of protein subcellular localization (SCL) is of key i...
Machine Learning Gene Expression Profiling Bacterial Proteins Gram-Negative Bacteria Computational Biology Databases, Protein Sequence Alignment Sequence Analysis, Protein Gram-Positive Bacteria Subcellular Fractions Molecular Sequence Annotation Gene Ontology
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Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

Interdisciplinary sciences, computational life sciences Jun 1, 2020
A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence abou...
Coronavirus 3C Proteases Structural Homology, Protein Betacoronavirus Pneumonia, Viral Catalytic Domain Oligopeptides Viral Nonstructural Proteins Cysteine Endopeptidases Databases, Pharmaceutical Pandemics Databases, Nucleic Acid COVID-19 Amino Acid Sequence Sequence Alignment SARS-CoV-2 Coronavirus Infections User-Computer Interface Ligands Antiviral Agents Drug Design Models, Molecular Humans Deep Learning Molecular Dynamics Simulation Drug Evaluation, Preclinical
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An Application of Random Walk Resampling to Phylogenetic HMM Inference and Learning.

IEEE transactions on nanobioscience May 8, 2020
Statistical resampling methods are widely used for confidence interval placement and as a data perturbation technique for statistical inference and learning. An important assumption of popular resampling methods such as the standard bootstrap is that...
Sequence Alignment Phylogeny Computational Biology Machine Learning Markov Chains Computer Simulation
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DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.

BMC bioinformatics Jan 9, 2020
BACKGROUND: Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on deep neural networks (DNNs) and multiple sequence alignments (MSAs) of target proteins. Protein seque...
Sequence Alignment Protein Structure, Tertiary Deep Learning Neural Networks, Computer User-Computer Interface Proteins Amino Acid Sequence Protein Structure, Secondary
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ProDCoNN: Protein design using a convolutional neural network.

Proteins Jan 6, 2020
Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this...
Sequence Alignment Neural Networks, Computer Amino Acid Sequence Datasets as Topic Protein Engineering Software Protein Structure, Secondary Proteins Databases, Protein
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Athena: Automated Tuning of k-mer based Genomic Error Correction Algorithms using Language Models.

Scientific reports Nov 6, 2019
The performance of most error-correction (EC) algorithms that operate on genomics reads is dependent on the proper choice of its configuration parameters, such as the value of k in k-mer based techniques. In this work, we target the problem of findin...
Datasets as Topic Automation Base Sequence Sequence Alignment Neural Networks, Computer Natural Language Processing Algorithms Oligonucleotides Genomics High-Throughput Nucleotide Sequencing
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