AIMC Topic: Proteins

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Boosted neural networks scoring functions for accurate ligand docking and ranking.

Journal of bioinformatics and computational biology Feb 4, 2018
Predicting the native poses of ligands correctly is one of the most important steps towards successful structure-based drug design. Binding affinities (BAs) estimated by traditional scoring functions (SFs) are typically used to score and rank-order p...
Ligands Escherichia coli Proteins tRNA Methyltransferases Proteins Databases, Protein Structure-Activity Relationship Neural Networks, Computer Machine Learning Algorithms Molecular Docking Simulation Drug Design Protein Binding
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Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines.

Computer methods and programs in biomedicine Feb 2, 2018
BACKGROUND AND OBJECTIVE: Discriminative and informative feature extraction is the core requirement for accurate and efficient classification of protein subcellular localization images so that drug development could be more effective. The objective o...
Support Vector Machine Computer Simulation Proteins Microscopy, Fluorescence Reproducibility of Results Subcellular Fractions Computational Biology
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Feature expansion by a continuous restricted Boltzmann machine for near-infrared spectrometric calibration.

Analytica chimica acta Jan 31, 2018
A modified algorithm for training a restricted Boltzmann machine (RBM) has been devised and demonstrated for improving the results for partial least squares (PLS) calibration of wheat and meat by near-infrared (NIR) spectroscopy. In all cases, the PL...
Spectroscopy, Near-Infrared Proteins Meat Least-Squares Analysis Machine Learning Calibration Algorithms Fats
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K: Protein-Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks.

Journal of chemical information and modeling Jan 29, 2018
Accurately predicting protein-ligand binding affinities is an important problem in computational chemistry since it can substantially accelerate drug discovery for virtual screening and lead optimization. We propose here a fast machine-learning appro...
Structure-Activity Relationship Deep Learning Models, Chemical Protein Binding Computational Biology Drug Discovery Ligands Proteins Databases, Protein
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Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Molecules (Basel, Switzerland) Jan 27, 2018
Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design initiatives which aim to counter the effects of serious diseases. Conducting mutagenesis studies in physical proteins can give insights about the effect...
Protein Stability Decision Trees Protein Conformation Thermodynamics Neural Networks, Computer Proteins Amino Acid Substitution Computer Simulation Mutation Support Vector Machine
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Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition.

Journal of chemical information and modeling Jan 10, 2018
Inspired by natural language processing techniques, we here introduce Mol2vec, which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Like the Word2vec models, where vectors of closely related w...
Algorithms Reproducibility of Results Proteins Models, Chemical Unsupervised Machine Learning Datasets as Topic Natural Language Processing Protein Conformation Molecular Structure
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Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.

PLoS computational biology Jan 8, 2018
This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules...
Area Under Curve Molecular Dynamics Simulation Ligands Models, Neurological Proteins Databases, Protein Nucleic Acids Static Electricity Protein Interaction Mapping Humans Neural Networks, Computer Machine Learning Algorithms Protein Binding Computational Biology
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ProtDet-CCH: Protein Remote Homology Detection by Combining Long Short-Term Memory and Ranking Methods.

IEEE/ACM transactions on computational biology and bioinformatics Jan 5, 2018
As one of the most challenging tasks in sequence analysis, protein remote homology detection has been extensively studied. Methods based on discriminative models and ranking approaches have achieved the state-of-the-art performance, and these two kin...
Sequence Analysis, Protein Databases, Protein Sequence Homology, Amino Acid Amino Acid Motifs Humans Neural Networks, Computer Software Computational Biology Support Vector Machine Proteins Algorithms Databases, Factual Reproducibility of Results
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Potent pairing: ensemble of long short-term memory networks and support vector machine for chemical-protein relation extraction.

Database : the journal of biological databases and curation Jan 1, 2018
Biomedical researchers regularly discover new interactions between chemical compounds/drugs and genes/proteins, and report them in research literature. Having knowledge about these interactions is crucially important in many research areas such as pr...
Databases, Protein Pharmaceutical Preparations Protein Binding Neural Networks, Computer Data Mining Databases, Chemical Drug Discovery Support Vector Machine Deep Learning Proteins
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Extracting chemical-protein relations using attention-based neural networks.

Database : the journal of biological databases and curation Jan 1, 2018
Relation extraction is an important task in the field of natural language processing. In this paper, we describe our approach for the BioCreative VI Task 5: text mining chemical-protein interactions. We investigate multiple deep neural network (DNN) ...
Proteins Neural Networks, Computer Databases, Protein Algorithms Databases, Chemical
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