AIMC Topic: Sequence Analysis, Protein

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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 ...
Amino Acids Internet Benchmarking Animals Models, Statistical Humans Cell-Penetrating Peptides Sequence Analysis, Protein Eukaryotic Cells Neural Networks, Computer Amino Acid Sequence Machine Learning Datasets as Topic Software Cell Membrane Permeability
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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...
Databases, Protein Sequence Analysis, Protein Software Membrane Proteins Support Vector Machine
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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...
Humans Machine Learning Algorithms Internet Sequence Analysis, Protein Protein Interaction Maps Computational Biology Proteins
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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...
Algorithms Sequence Analysis, Protein Amyloidogenic Proteins Support Vector Machine Databases, Protein Internet Reproducibility of Results Computational Biology
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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...
Support Vector Machine Protein Domains Sequence Analysis, Protein Software Animals Oxidative Stress Humans
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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...
Eukaryota Sequence Analysis, Protein Data Mining Semantics Gene Ontology Computational Biology Proteins Humans Machine Learning Animals
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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...
Humans Animals Deep Learning Solubility Hydrophobic and Hydrophilic Interactions Protein Conformation Sequence Analysis, Protein
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Prediction of lysine glutarylation sites by maximum relevance minimum redundancy feature selection.

Analytical biochemistry Apr 8, 2018
Lysine glutarylation is new type of protein acylation modification in both prokaryotes and eukaryotes. To better understand the molecular mechanism of glutarylation, it is important to identify glutarylated substrates and their corresponding glutaryl...
Software Support Vector Machine Glutarates Protein Processing, Post-Translational Sequence Analysis, Protein Acylation Proteins Lysine
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The Impact of Protein Structure and Sequence Similarity on the Accuracy of Machine-Learning Scoring Functions for Binding Affinity Prediction.

Biomolecules Mar 14, 2018
It has recently been claimed that the outstanding performance of machine-learning scoring functions (SFs) is exclusively due to the presence of training complexes with highly similar proteins to those in the test set. Here, we revisit this question u...
Protein Interaction Mapping Machine Learning Sequence Analysis, Protein Molecular Docking Simulation
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MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

Journal of molecular biology Mar 10, 2018
Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO,...
Amino Acid Sequence Protein Conformation Algorithms Gene Ontology Models, Molecular Protein Interaction Mapping Reproducibility of Results Internet Sequence Homology, Amino Acid Software Protein Interaction Maps Sequence Analysis, Protein Computational Biology Proteins
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