AIMC Topic: Proteins

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Prediction of protein-protein interaction sites from weakly homologous template structures using meta-threading and machine learning.

Journal of molecular recognition : JMR Jan 1, 2015
The identification of protein-protein interactions is vital for understanding protein function, elucidating interaction mechanisms, and for practical applications in drug discovery. With the exponentially growing protein sequence data, fully automate...
Evolution, Molecular Algorithms Proteins Protein Binding Models, Molecular Hydrogen Bonding Machine Learning Binding Sites Software
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Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

Combinatorial chemistry & high throughput screening Jan 1, 2015
The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties o...
Proteins Models, Biological Artificial Intelligence Quantitative Structure-Activity Relationship Informatics Drug Design
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Computer-Aided Virtual Screening and Designing of Cell-Penetrating Peptides.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Cell-penetrating peptides (CPPs) have proven their potential as versatile drug delivery vehicles. Last decade has witnessed an unprecedented growth in CPP-based research, demonstrating the potential of CPPs as therapeutic candidates. In the past, man...
Cell-Penetrating Peptides Molecular Sequence Data Machine Learning Proteins Drug Carriers Computer-Aided Design Amino Acid Motifs Computer Simulation Amino Acid Sequence Support Vector Machine Humans Animals
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Constructing query-driven dynamic machine learning model with application to protein-ligand binding sites prediction.

IEEE transactions on nanobioscience Jan 1, 2015
We are facing an era with annotated biological data rapidly and continuously generated. How to effectively incorporate new annotated data into the learning step is crucial for enhancing the performance of a bioinformatics prediction model. Although m...
Machine Learning Protein Binding Binding Sites Models, Biological Proteins Nucleotides Databases, Protein Ligands
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Advances in protein contact map prediction based on machine learning.

Medicinal chemistry (Shariqah (United Arab Emirates)) Jan 1, 2015
A protein contact map is a simplified, two-dimensional version of the three-dimensional protein structure. Protein contact map is proved to be crucial in forming the three-dimensional structure. Contact map prediction has now become an indispensable ...
Proteins Protein Conformation Neural Networks, Computer Algorithms Computational Biology Machine Learning
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Some remarks on prediction of protein-protein interaction with machine learning.

Medicinal chemistry (Shariqah (United Arab Emirates)) Jan 1, 2015
Protein-protein interactions (PPIs) play a key role in many cellular processes. Uncovering the PPIs and their function within the cell is a challenge of post-genomic biology and will improve our understanding of disease and help in the development of...
Protein Binding Proteins High-Throughput Screening Assays Machine Learning Algorithms
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Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...
Image Processing, Computer-Assisted Computational Biology Proteins Algorithms Drug Discovery Protein Conformation Nerve Net Models, Biological Tuberculosis Humans Neural Networks, Computer
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GENN: a GEneral Neural Network for learning tabulated data with examples from protein structure prediction.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
We present a GEneral Neural Network (GENN) for learning trends from existing data and making predictions of unknown information. The main novelty of GENN is in its generality, simplicity of use, and its specific handling of windowed input/output. Its...
Neural Networks, Computer Proteins Models, Molecular Protein Conformation Software Computational Biology
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Protein structural information derived from NMR chemical shift with the neural network program TALOS-N.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trai...
Carbon Isotopes Protein Conformation Nuclear Magnetic Resonance, Biomolecular Neural Networks, Computer Software Proteomics Proteins Models, Molecular
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Introduction to the analysis of the intracellular sorting information in protein sequences: from molecular biology to artificial neural networks.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
A precise spatial-temporal organization of cell components is required for basic cellular activities such as proliferation and for complex multicellular processes such as embryo development. Particularly important is the maintenance and control of th...
Neural Networks, Computer Proteomics Protein Transport Protein Sorting Signals Cytoplasmic Vesicles Proteins Databases, Protein
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