AIMC Topic: Databases, Protein

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SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

PloS one Aug 15, 2016
Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine l...
Sequence Alignment Databases, Protein Internet Amino Acid Sequence Computational Biology Support Vector Machine Proteins
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OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method.

Journal of computational biology : a journal of computational molecular cell biology Aug 11, 2016
In the two transmembrane protein types, outer membrane proteins (OMPs) perform diverse important biochemical functions, including substrate transport and passive nutrient uptake and intake. Hence their 3D structures are expected to reveal these funct...
Support Vector Machine Databases, Protein Protein Conformation, beta-Strand Protein Structure, Tertiary Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Biological Transport Bacterial Outer Membrane Proteins Membrane Lipids
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Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.

Protein science : a publication of the Protein Society Aug 9, 2016
Predicting protein-protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high...
Algorithms Protein Binding Saccharomyces cerevisiae Bacterial Proteins Support Vector Machine Saccharomyces cerevisiae Proteins Helicobacter pylori Databases, Protein
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In Silico Prediction of Gamma-Aminobutyric Acid Type-A Receptors Using Novel Machine-Learning-Based SVM and GBDT Approaches.

BioMed research international Aug 8, 2016
Gamma-aminobutyric acid type-A receptors (GABAARs) belong to multisubunit membrane spanning ligand-gated ion channels (LGICs) which act as the principal mediators of rapid inhibitory synaptic transmission in the human brain. Therefore, the category p...
Computational Biology Support Vector Machine Amino Acids Ligands Humans Decision Making Brain Models, Statistical Machine Learning Amino Acid Motifs Computer Simulation Decision Trees Algorithms Receptors, GABA-A Reproducibility of Results Databases, Protein
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Positive-Unlabeled Learning for Pupylation Sites Prediction.

BioMed research international Aug 7, 2016
Pupylation plays a key role in regulating various protein functions as a crucial posttranslational modification of prokaryotes. In order to understand the molecular mechanism of pupylation, it is important to identify pupylation substrates and sites ...
Lysine Protein Processing, Post-Translational Binding Sites Proteins Machine Learning Databases, Protein Ubiquitination Algorithms Support Vector Machine
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Revealing disease-associated pathways by network integration of untargeted metabolomics.

Nature methods Aug 1, 2016
Uncovering the molecular context of dysregulated metabolites is crucial to understand pathogenic pathways. However, their system-level analysis has been limited owing to challenges in global metabolite identification. Most metabolite features detecte...
Sphingolipids Humans Huntington Disease Neural Networks, Computer Databases, Protein Steroids Machine Learning Metabolic Networks and Pathways Algorithms Metabolomics Fatty Acids
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A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.

International journal of molecular sciences Jul 27, 2016
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous publ...
Protein Interaction Domains and Motifs Databases, Protein Protein Conformation Protein Interaction Mapping Humans Computational Biology Machine Learning Proteins Algorithms
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Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass Spectra.

Journal of proteome research Jul 22, 2016
A central problem in mass spectrometry analysis involves identifying, for each observed tandem mass spectrum, the corresponding generating peptide. We present a dynamic Bayesian network (DBN) toolkit that addresses this problem by using a machine lea...
Machine Learning Software Bayes Theorem Tandem Mass Spectrometry Peptides Proteomics Databases, Protein
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Machine Learning of Protein Interactions in Fungal Secretory Pathways.

PloS one Jul 21, 2016
In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict prote...
Machine Learning Algorithms Genome, Fungal Secretory Pathway ROC Curve Saccharomyces cerevisiae Protein Interaction Maps Trichoderma Evolution, Molecular Protein Interaction Mapping Databases, Protein Amino Acid Sequence Fungal Proteins
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An improved method for predicting interactions between virus and human proteins.

Journal of bioinformatics and computational biology Jul 10, 2016
The interaction of virus proteins with host proteins plays a key role in viral infection and consequent pathogenesis. Many computational methods have been proposed to predict protein-protein interactions (PPIs), but most of the computational methods ...
Alphapapillomavirus Gene Ontology Viral Proteins Protein Interaction Mapping Computational Biology Support Vector Machine Databases, Protein Amino Acids Hepacivirus Host-Pathogen Interactions Humans Reproducibility of Results
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