AIMC Topic: Sequence Analysis, Protein

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Enhancing the Prediction of Transmembrane β-Barrel Segments with Chain Learning and Feature Sparse Representation.

IEEE/ACM transactions on computational biology and bioinformatics Feb 11, 2016
Transmembrane β-barrels (TMBs) are one important class of membrane proteins that play crucial functions in the cell. Membrane proteins are difficult wet-lab targets of structural biology, which call for accurate computational prediction approaches. H...
Computer Simulation Membrane Proteins Databases, Protein Machine Learning Algorithms Protein Structure, Secondary Molecular Sequence Data Sequence Analysis, Protein Models, Chemical Amino Acid Sequence Pattern Recognition, Automated
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UbiSite: incorporating two-layered machine learning method with substrate motifs to predict ubiquitin-conjugation site on lysines.

BMC systems biology Jan 11, 2016
BACKGROUND: The conjugation of ubiquitin to a substrate protein (protein ubiquitylation), which involves a sequential process--E1 activation, E2 conjugation and E3 ligation, is crucial to the regulation of protein function and activity in eukaryotes....
Machine Learning Sequence Analysis, Protein Amino Acid Sequence Datasets as Topic Lysine Ubiquitin Ubiquitination Amino Acid Motifs Mass Spectrometry Models, Molecular Protein Domains Software Proteomics Proteome
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Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine.

PloS one Dec 4, 2015
The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of ...
Protein Binding Viral Envelope Proteins Support Vector Machine Sequence Analysis, Protein Peptide Fragments Viral Fusion Protein Inhibitors
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A Sequence-Based Dynamic Ensemble Learning System for Protein Ligand-Binding Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 3, 2015
BACKGROUND: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands...
Proteins Data Interpretation, Statistical Models, Chemical Algorithms Molecular Docking Simulation Protein Binding Protein Interaction Mapping Sequence Analysis, Protein Ligands Pattern Recognition, Automated Binding Sites Machine Learning
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Prediction the Substrate Specificities of Membrane Transport Proteins Based on Support Vector Machine and Hybrid Features.

IEEE/ACM transactions on computational biology and bioinformatics Nov 11, 2015
Membrane transport proteins and their substrate specificities play crucial roles in a variety of cellular functions. Identifying the substrate specificities of membrane transport proteins is closely related to the protein-target interaction predictio...
Membrane Transport Proteins Binding Sites Substrate Specificity Protein Interaction Mapping Sequence Analysis, Protein Support Vector Machine Models, Chemical Pattern Recognition, Automated Algorithms Molecular Docking Simulation Protein Binding
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Unsupervised learning assisted robust prediction of bioluminescent proteins.

Computers in biology and medicine Nov 10, 2015
Bioluminescence plays an important role in nature, for example, it is used for intracellular chemical signalling in bacteria. It is also used as a useful reagent for various analytical research methods ranging from cellular imaging to gene expression...
Machine Learning Algorithms Predictive Value of Tests Sequence Analysis, Protein Luminescent Proteins
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Computational probing protein-protein interactions targeting small molecules.

Bioinformatics (Oxford, England) Sep 28, 2015
MOTIVATION: With the booming of interactome studies, a lot of interactions can be measured in a high throughput way and large scale datasets are available. It is becoming apparent that many different types of interactions can be potential drug target...
Pharmaceutical Preparations Protein Interaction Mapping Sequence Analysis, Protein Drug Discovery Support Vector Machine Proteins Humans Algorithms
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MDD-SOH: exploiting maximal dependence decomposition to identify S-sulfenylation sites with substrate motifs.

Bioinformatics (Oxford, England) Sep 26, 2015
UNLABELLED: S-sulfenylation (S-sulphenylation, or sulfenic acid), the covalent attachment of S-hydroxyl (-SOH) to cysteine thiol, plays a significant role in redox regulation of protein functions. Although sulfenic acid is transient and labile, most ...
Humans Software Support Vector Machine Sulfur Acids Cysteine Protein Processing, Post-Translational Amino Acid Motifs Proteins Sequence Analysis, Protein Amino Acids
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DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool.

Nucleic acids research Aug 24, 2015
There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provi...
Arabidopsis Molecular Sequence Annotation Genome, Plant Sequence Analysis, Protein Support Vector Machine Models, Biological Solanum lycopersicum Plant Proteins DNA-Binding Proteins Species Specificity
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Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

Bioinformatics (Oxford, England) Aug 14, 2015
MOTIVATION: Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However...
Sequence Analysis, Protein Machine Learning Software Proteins Protein Conformation Algorithms Sequence Alignment Models, Statistical Evolution, Molecular
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