AIMC Topic: Proteins

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An Enhanced Protein Fold Recognition for Low Similarity Datasets Using Convolutional and Skip-Gram Features With Deep Neural Network.

IEEE transactions on nanobioscience Dec 30, 2020
The protein fold recognition is one of the important tasks of structural biology, which helps in addressing further challenges like predicting the protein tertiary structures and its functions. Many machine learning works are published to identify th...
Machine Learning Proteins Neural Networks, Computer
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Template-based prediction of protein structure with deep learning.

BMC genomics Dec 29, 2020
BACKGROUND: Accurate prediction of protein structure is fundamentally important to understand biological function of proteins. Template-based modeling, including protein threading and homology modeling, is a popular method for protein tertiary struct...
Proteins Databases, Protein Protein Conformation Sequence Analysis, Protein Algorithms Deep Learning Software
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Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts.

Journal of chemical information and modeling Dec 21, 2020
Predicting compound-protein affinity is beneficial for accelerating drug discovery. Doing so without the often-unavailable structure data is gaining interest. However, recent progress in structure-free affinity prediction, made by machine learning, f...
Deep Learning Proteins Amino Acid Sequence Neural Networks, Computer Machine Learning
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Artificial intelligence in the early stages of drug discovery.

Archives of biochemistry and biophysics Dec 19, 2020
Although the use of computational methods within the pharmaceutical industry is well established, there is an urgent need for new approaches that can improve and optimize the pipeline of drug discovery and development. In spite of the fact that there...
Drug Discovery Deep Learning Humans Animals Proteins Drug Repositioning Protein Binding Cell Line Pharmaceutical Preparations Ligands
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Inter-protein residue covariation information unravels physically interacting protein dimers.

BMC bioinformatics Dec 17, 2020
BACKGROUND: Predicting physical interaction between proteins is one of the greatest challenges in computational biology. There are considerable various protein interactions and a huge number of protein sequences and synthetic peptides with unknown in...
Proteins Databases, Protein Support Vector Machine Protein Interaction Maps Evolution, Molecular Dimerization
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Bioimage-Based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2020
Prediction of protein subcellular location has currently become a hot topic because it has been proven to be useful for understanding both the disease mechanisms and novel drug design. With the rapid development of automated microscopic imaging techn...
Intracellular Space Image Processing, Computer-Assisted Proteomics Proteins Algorithms Humans Organ Specificity Deep Learning
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Target-Specific Drug Design Method Combining Deep Learning and Water Pharmacophore.

Journal of chemical information and modeling Nov 30, 2020
Following identification of a target protein, hit identification, which finds small organic molecules that bind to the target, is an important first step of a structure-based drug design project. In this study, we demonstrate a target-specific drug d...
Drug Design Deep Learning Algorithms Ligands Molecular Docking Simulation Water Proteins
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Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networks.

PLoS computational biology Nov 30, 2020
Predicting mutation-induced changes in protein thermodynamic stability (ΔΔG) is of great interest in protein engineering, variant interpretation, and protein biophysics. We introduce ThermoNet, a deep, 3D-convolutional neural network (3D-CNN) designe...
Proteins Protein Stability Imaging, Three-Dimensional Neural Networks, Computer Thermodynamics Computational Biology Point Mutation
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DeepPSP: A Global-Local Information-Based Deep Neural Network for the Prediction of Protein Phosphorylation Sites.

Journal of proteome research Nov 26, 2020
Identification of phosphorylation sites is an important step in the function study and drug design of proteins. In recent years, there have been increasing applications of the computational method in the identification of phosphorylation sites becaus...
Phosphorylation Amino Acid Sequence Computational Biology Proteins Neural Networks, Computer
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An artificial intelligence process of immunoassay for multiple biomarkers based on logic gates.

The Analyst Nov 25, 2020
We present a universal platform to synchronously analyze the possible existing state of two protein biomarkers. This platform is based on the integration of three logic gates: NAND, OR and NOT. These logic gates were constructed by the principle of i...
Artificial Intelligence Biomarkers Proteins Immunoassay Logic
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