AIMC Topic: Sequence Analysis, Protein

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Decision-Tree Based Meta-Strategy Improved Accuracy of Disorder Prediction and Identified Novel Disordered Residues Inside Binding Motifs.

International journal of molecular sciences Oct 7, 2018
Using computational techniques to identify intrinsically disordered residues is practical and effective in biological studies. Therefore, designing novel high-accuracy strategies is always preferable when existing strategies have a lot of room for im...
Software Intrinsically Disordered Proteins Sequence Analysis, Protein Humans Neural Networks, Computer
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Predicting improved protein conformations with a temporal deep recurrent neural network.

PloS one Sep 4, 2018
Accurate protein structure prediction from amino acid sequence is still an unsolved problem. The most reliable methods centre on template based modelling. However, the accuracy of these models entirely depends on the availability of experimentally re...
Amino Acid Sequence Protein Conformation Sequence Analysis, Protein Algorithms Deep Learning Protein Folding Neural Networks, Computer Molecular Dynamics Simulation Software
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BlaPred: Predicting and classifying β-lactamase using a 3-tier prediction system via Chou's general PseAAC.

Journal of theoretical biology Aug 20, 2018
Antibiotics of β-lactam class account for nearly half of the global antibiotic use. The β-lactamase enzyme is a major element of the bacterial arsenals to escape the lethal effect of β-lactam antibiotics. Different variants of β-lactamases have evolv...
Support Vector Machine beta-Lactamases beta-Lactam Resistance Sequence Analysis, Protein Databases, Protein Bacterial Proteins
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KELM-CPPpred: Kernel Extreme Learning Machine Based Prediction Model for Cell-Penetrating Peptides.

Journal of proteome research Aug 13, 2018
Cell-penetrating peptides (CPPs) facilitate the transport of pharmacologically active molecules, such as plasmid DNA, short interfering RNA, nanoparticles, and small peptides. The accurate identification of new and unique CPPs is the initial step to ...
Cell-Penetrating Peptides Sequence Analysis, Protein Eukaryotic Cells Datasets as Topic Cell Membrane Permeability Benchmarking Internet Humans Amino Acid Sequence Neural Networks, Computer Models, Statistical Amino Acids Machine Learning Software Animals
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Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC.

Journal of theoretical biology Jul 27, 2018
Membrane proteins are vital type of proteins that serve as channels, receptors and energy transducers in a cell. They perform various important functions, which are mainly associated with their types. They are also attractive targets of drug discover...
Support Vector Machine Databases, Protein Sequence Analysis, Protein Software Membrane Proteins
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PROSES: A Web Server for Sequence-Based Protein Encoding.

Journal of computational biology : a journal of computational molecular cell biology Jul 27, 2018
Recently, the number of the amino acid sequences shared in online databases is growing rapidly in huge amounts. By using sequence-derived features, machine learning algorithms are successfully applied to prediction of protein functional classes, prot...
Sequence Analysis, Protein Computational Biology Proteins Internet Algorithms Protein Interaction Maps Humans Machine Learning
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RFAmyloid: A Web Server for Predicting Amyloid Proteins.

International journal of molecular sciences Jul 16, 2018
Amyloid is an insoluble fibrous protein and its mis-aggregation can lead to some diseases, such as Alzheimer's disease and Creutzfeldt⁻Jakob's disease. Therefore, the identification of amyloid is essential for the discovery and understanding of disea...
Sequence Analysis, Protein Amyloidogenic Proteins Databases, Protein Internet Algorithms Computational Biology Support Vector Machine Reproducibility of Results
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SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins.

International journal of molecular sciences Jun 15, 2018
Antioxidant proteins can be beneficial in disease prevention. More attention has been paid to the functionality of antioxidant proteins. Therefore, identifying antioxidant proteins is important for the study. In our work, we propose a computational m...
Sequence Analysis, Protein Support Vector Machine Protein Domains Software Humans Animals Oxidative Stress
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DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

Methods (San Diego, Calif.) Jun 6, 2018
As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to r...
Animals Computational Biology Data Mining Semantics Proteins Humans Machine Learning Sequence Analysis, Protein Gene Ontology Eukaryota
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Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network.

Biomolecules May 25, 2018
Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep lear...
Solubility Humans Hydrophobic and Hydrophilic Interactions Protein Conformation Sequence Analysis, Protein Animals Deep Learning
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