AIMC Topic: Sequence Analysis, Protein

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Protein structure modeling and refinement by global optimization in CASP12.

Proteins Dec 5, 2017
For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequ...
Computational Biology Support Vector Machine Models, Statistical Proteins Humans Machine Learning Algorithms Protein Conformation Protein Folding Sequence Analysis, Protein Protein Interaction Domains and Motifs Models, Molecular Molecular Dynamics Simulation Crystallography, X-Ray
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Assessment of the model refinement category in CASP12.

Proteins Nov 29, 2017
We here report on the assessment of the model refinement predictions submitted to the 12th Experiment on the Critical Assessment of Protein Structure Prediction (CASP12). This is the fifth refinement experiment since CASP8 (2008) and, as with the pre...
Computational Biology Proteins Models, Molecular Protein Folding Sequence Analysis, Protein Crystallography, X-Ray Humans Machine Learning Protein Conformation Algorithms
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Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants.

Proteins Nov 29, 2017
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predic...
PTEN Phosphohydrolase Models, Biological Gene Ontology Sequence Analysis, Protein Humans Machine Learning Proteomics Databases, Protein Animals Transcriptome
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Classification of G-protein coupled receptors based on a rich generation of convolutional neural network, N-gram transformation and multiple sequence alignments.

Amino acids Nov 18, 2017
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithm...
Sequence Analysis, Protein Receptors, G-Protein-Coupled Amino Acid Sequence Sequence Alignment Machine Learning Reproducibility of Results Algorithms Models, Theoretical Databases, Protein Neural Networks, Computer
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Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12.

Proteins Nov 14, 2017
We develop two complementary pipelines, "Zhang-Server" and "QUARK", based on I-TASSER and QUARK pipelines for template-based modeling (TBM) and free modeling (FM), and test them in the CASP12 experiment. The combination of I-TASSER and QUARK successf...
Humans Machine Learning Databases, Protein Models, Molecular Crystallography, X-Ray Protein Conformation Algorithms Computational Biology Proteins Protein Folding Sequence Alignment Sequence Analysis, Protein
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Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

Proteins Oct 31, 2017
In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on co...
Models, Molecular Datasets as Topic Crystallography, X-Ray Computational Biology Sequence Alignment Proteins Sequence Analysis, Protein Protein Conformation Databases, Protein Protein Folding Humans Machine Learning Algorithms
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Simultaneous refinement of inaccurate local regions and overall structure in the CASP12 protein model refinement experiment.

Proteins Oct 26, 2017
Advances in protein model refinement techniques are required as diverse sources of protein structure information are available from low-resolution experiments or informatics-based computations such as cryo-EM, NMR, homology models, or predicted resid...
Crystallography, X-Ray Computational Biology Humans Protein Interaction Domains and Motifs Models, Molecular Proteins Protein Conformation Machine Learning Molecular Dynamics Simulation Algorithms Sequence Analysis, Protein
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Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.

PLoS computational biology Oct 23, 2017
There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilay...
Machine Learning Drug Design Structure-Activity Relationship Humans HEK293 Cells Subcellular Fractions Sequence Analysis, Protein Cell Membrane Rhodopsin Ion Channels Lipid Bilayers
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A Computational-Based Method for Predicting Drug-Target Interactions by Using Stacked Autoencoder Deep Neural Network.

Journal of computational biology : a journal of computational molecular cell biology Sep 11, 2017
Identifying the interaction between drugs and target proteins is an important area of drug research, which provides a broad prospect for low-risk and faster drug development. However, due to the limitations of traditional experiments when revealing d...
Databases, Chemical Deep Learning Reproducibility of Results Sequence Analysis, Protein Protein Binding Molecular Docking Simulation
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Prediction of N-linked glycosylation sites using position relative features and statistical moments.

PloS one Aug 10, 2017
Glycosylation is one of the most complex post translation modification in eukaryotic cells. Almost 50% of the human proteome is glycosylated as glycosylation plays a vital role in various biological functions such as antigen's recognition, cell-cell ...
Databases, Protein Computational Biology Humans Amino Acid Sequence Glycosylation Neural Networks, Computer Sequence Analysis, Protein Support Vector Machine Algorithms
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