AIMC Topic: Protein Interaction Mapping

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Using deep maxout neural networks to improve the accuracy of function prediction from protein interaction networks.

PloS one Jul 23, 2019
Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend ...
Humans Neural Networks, Computer Protein Interaction Maps Computational Biology Proteins Protein Interaction Mapping
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An Ensemble Classifier to Predict Protein-Protein Interactions by Combining PSSM-based Evolutionary Information with Local Binary Pattern Model.

International journal of molecular sciences Jul 17, 2019
Protein plays a critical role in the regulation of biological cell functions. Among them, whether proteins interact with each other has become a fundamental problem, because proteins usually perform their functions by interacting with other proteins....
Position-Specific Scoring Matrices Support Vector Machine Databases, Protein Humans Protein Interaction Mapping Software Computational Biology
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Automated feature engineering improves prediction of protein-protein interactions.

Amino acids Jul 5, 2019
Over the last decade, various machine learning (ML) and statistical approaches for protein-protein interaction (PPI) predictions have been developed to help annotating functional interactions among proteins, essential for our system-level understandi...
Humans Support Vector Machine Software Machine Learning Proteins Algorithms Protein Interaction Mapping Computational Biology
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Glioma stages prediction based on machine learning algorithm combined with protein-protein interaction networks.

Genomics May 29, 2019
BACKGROUND: Glioma is the most lethal nervous system cancer. Recent studies have made great efforts to study the occurrence and development of glioma, but the molecular mechanisms are still unclear. This study was designed to reveal the molecular mec...
Brain Neoplasms Neoplasm Staging Gene Ontology Glioma Machine Learning Gene Expression Protein Interaction Mapping
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A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence.

Mathematical biosciences Apr 25, 2019
Protein-protein interactions (PPIs) play a crucial role in the life-sustaining activities of organisms. Although various methods for the prediction of PPIs have been developed in the past decades, their robustness and prediction accuracy need to be i...
Computational Biology Amino Acid Sequence Protein Interaction Mapping Humans Neural Networks, Computer Animals
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Machine-Learning-Based Predictor of Human-Bacteria Protein-Protein Interactions by Incorporating Comprehensive Host-Network Properties.

Journal of proteome research Apr 22, 2019
The large-scale identification of protein-protein interactions (PPIs) between humans and bacteria remains a crucial step in systematically understanding the underlying molecular mechanisms of bacterial infection. Computational prediction approaches a...
Area Under Curve Gene Expression Bacterial Proteins Proteome Models, Statistical Databases, Protein Bacillus anthracis Eukaryotic Cells Molecular Mimicry Host-Pathogen Interactions Yersinia pestis Protein Interaction Mapping Humans Machine Learning Protein Binding Francisella tularensis
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Predicting protein-peptide interaction sites using distant protein complexes as structural templates.

Scientific reports Mar 12, 2019
Protein-peptide interactions play an important role in major cellular processes, and are associated with several human diseases. To understand and potentially regulate these cellular function and diseases it is important to know the molecular details...
Binding Sites Protein Interaction Mapping Protein Binding Computational Biology Cluster Analysis Proteins Amino Acid Sequence Datasets as Topic Humans Software Machine Learning Peptides Molecular Docking Simulation
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Gene ontology improves template selection in comparative protein docking.

Proteins Dec 27, 2018
Structural characterization of protein-protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and a...
Humans Software Structural Homology, Protein Computational Biology Gene Ontology Molecular Docking Simulation Proteins Models, Molecular Binding Sites Protein Interaction Maps Databases, Protein Protein Conformation Protein Interaction Mapping Protein Binding
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Prediction of protein self-interactions using stacked long short-term memory from protein sequences information.

BMC systems biology Dec 21, 2018
BACKGROUND: Self-interacting Proteins (SIPs) plays a critical role in a series of life function in most living cells. Researches on SIPs are important part of molecular biology. Although numerous SIPs data be provided, traditional experimental method...
Protein Interaction Mapping Neural Networks, Computer Computational Biology Saccharomyces cerevisiae Humans
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Integrating network topology, gene expression data and GO annotation information for protein complex prediction.

Journal of bioinformatics and computational biology Oct 30, 2018
The prediction of protein complexes based on the protein interaction network is a fundamental task for the understanding of cellular life as well as the mechanisms underlying complex disease. A great number of methods have been developed to predict p...
Databases, Protein Protein Interaction Maps Saccharomyces cerevisiae Proteins Gene Ontology Computational Biology Multiprotein Complexes Protein Interaction Mapping Cluster Analysis Algorithms Transcriptome
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