AIMC Topic: Amino Acid Sequence

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Prediction of zinc-binding sites using multiple sequence profiles and machine learning methods.

Molecular omics May 2, 2019
The zinc (Zn) cofactor has been proven to be involved in numerous biological mechanisms and the zinc-binding site is recognized as one of the most important post-translation modifications in proteins. Therefore, accurate knowledge of zinc ions in pro...
Zinc Protein Binding Computational Biology Software Algorithms Computer Simulation Protein Conformation Binding Sites Protein Folding Support Vector Machine Databases, Protein Amino Acid Sequence Machine Learning
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A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence.

Mathematical biosciences Apr 25, 2019
Protein-protein interactions (PPIs) play a crucial role in the life-sustaining activities of organisms. Although various methods for the prediction of PPIs have been developed in the past decades, their robustness and prediction accuracy need to be i...
Protein Interaction Mapping Animals Computational Biology Amino Acid Sequence Humans Neural Networks, Computer
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Deep Robust Framework for Protein Function Prediction Using Variable-Length Protein Sequences.

IEEE/ACM transactions on computational biology and bioinformatics Apr 16, 2019
The order of amino acids in a protein sequence enables the protein to acquire a conformation suitable for performing functions, thereby motivating the need to analyze these sequences for predicting functions. Although machine learning based approache...
Amino Acid Sequence Protein Conformation Sequence Analysis, Protein Algorithms Deep Learning Computational Biology Proteins Discriminant Analysis
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Machine learning-assisted directed protein evolution with combinatorial libraries.

Proceedings of the National Academy of Sciences of the United States of America Apr 12, 2019
To reduce experimental effort associated with directed protein evolution and to explore the sequence space encoded by mutating multiple positions simultaneously, we incorporate machine learning into the directed evolution workflow. Combinatorial sequ...
Humans Machine Learning Models, Molecular Small Molecule Libraries Combinatorial Chemistry Techniques Oxygenases Amino Acid Sequence Protein Conformation Directed Molecular Evolution Rhodothermus
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Seq2seq Fingerprint with Byte-Pair Encoding for Predicting Changes in Protein Stability upon Single Point Mutation.

IEEE/ACM transactions on computational biology and bioinformatics Apr 1, 2019
The engineering of stable proteins is crucial for various industrial purposes. Several machine learning methods have been developed to predict changes in the stability of proteins corresponding to single point mutations. To improve the prediction acc...
Unsupervised Machine Learning Amino Acid Sequence Protein Stability Sequence Analysis, Protein Point Mutation Computational Biology Humans Databases, Genetic Neural Networks, Computer Proteins
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NeuroPIpred: a tool to predict, design and scan insect neuropeptides.

Scientific reports Mar 26, 2019
Insect neuropeptides and their associated receptors have been one of the potential targets for the pest control. The present study describes in silico models developed using natural and modified insect neuropeptides for predicting and designing new n...
Neuropeptides Sequence Analysis, Protein Support Vector Machine Humans Databases, Protein Software Amino Acid Sequence Animals
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Predicting drug-target interaction network using deep learning model.

Computational biology and chemistry Mar 25, 2019
BACKGROUND: Traditional methods for drug discovery are time-consuming and expensive, so efforts are being made to repurpose existing drugs. To find new ways for drug repurposing, many computational approaches have been proposed to predict drug-target...
Proteins Databases, Protein Breast Neoplasms Amino Acid Sequence Protein Binding Molecular Structure Antineoplastic Agents Databases, Chemical Drug Repositioning Computational Biology Models, Chemical Deep Learning Genes, Neoplasm Protein Domains Support Vector Machine
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Predicting protein residue-residue contacts using random forests and deep networks.

BMC bioinformatics Mar 14, 2019
BACKGROUND: The ability to predict which pairs of amino acid residues in a protein are in contact with each other offers many advantages for various areas of research that focus on proteins. For example, contact prediction can be used to reduce the c...
Machine Learning Computational Biology Proteins Amino Acid Sequence
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Predicting protein-peptide interaction sites using distant protein complexes as structural templates.

Scientific reports Mar 12, 2019
Protein-peptide interactions play an important role in major cellular processes, and are associated with several human diseases. To understand and potentially regulate these cellular function and diseases it is important to know the molecular details...
Computational Biology Protein Interaction Mapping Cluster Analysis Proteins Peptides Amino Acid Sequence Datasets as Topic Molecular Docking Simulation Binding Sites Protein Binding Humans Machine Learning Software
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Predicting protein-ligand binding residues with deep convolutional neural networks.

BMC bioinformatics Feb 26, 2019
BACKGROUND: Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categ...
Databases, Protein Deep Learning Amino Acid Sequence Protein Binding Neural Networks, Computer Ligands Proteins Algorithms
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