AIMC Topic: Proteins

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predCar-site: Carbonylation sites prediction in proteins using support vector machine with resolving data imbalanced issue.

Analytical biochemistry Mar 9, 2017
The carbonylation is found as an irreversible post-translational modification and considered a biomarker of oxidative stress. It plays major role not only in orchestrating various biological processes but also associated with some diseases such as Al...
Protein Carbonylation Sequence Analysis, Protein Algorithms Computational Biology Support Vector Machine Protein Processing, Post-Translational Proteins Models, Biological Humans Software
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Active learning for computational chemogenomics.

Future medicinal chemistry Mar 6, 2017
AIM: Computational chemogenomics models the compound-protein interaction space, typically for drug discovery, where existing methods predominantly either incorporate increasing numbers of bioactivity samples or focus on specific subfamilies of protei...
Computer Simulation Drug Discovery Genomics Machine Learning Ligands Databases, Chemical Binding Sites Computational Biology Proteins Models, Chemical
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Improved prediction of protein-protein interactions using novel negative samples, features, and an ensemble classifier.

Artificial intelligence in medicine Mar 4, 2017
Computational methods are employed in bioinformatics to predict protein-protein interactions (PPIs). PPIs and protein-protein non-interactions (PPNIs) display different levels of development, and the number of PPIs is considerably greater than that o...
Computational Biology Proteins Databases, Protein Humans Reproducibility of Results Protein Interaction Maps Protein Structure, Secondary Structure-Activity Relationship Natural Language Processing Amino Acid Sequence
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A novel hierarchical selective ensemble classifier with bioinformatics application.

Artificial intelligence in medicine Feb 27, 2017
Selective ensemble learning is a technique that selects a subset of diverse and accurate basic models in order to generate stronger generalization ability. In this paper, we proposed a novel learning algorithm that is based on parallel optimization a...
Data Mining RNA, Transfer ROC Curve Protein Interaction Maps Computational Biology Machine Learning Databases, Genetic Reproducibility of Results Proteins Area Under Curve
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A Hybrid Knowledge-Based and Empirical Scoring Function for Protein-Ligand Interaction: SMoG2016.

Journal of chemical information and modeling Feb 27, 2017
We present the third generation of our scoring function for the prediction of protein-ligand binding free energy. This function is now a hybrid between a knowledge-based potential and an empirical function. We constructed a diversified set of ∼1000 c...
Models, Molecular Knowledge Bases Ligands Probability Protein Conformation Entropy Protein Binding Proteins Databases, Protein
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SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PloS one Feb 13, 2017
Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such ...
Receptors, G-Protein-Coupled Humans Molecular Targeted Therapy Internet Algorithms Pharmaceutical Preparations Models, Theoretical Reproducibility of Results Protein Binding Support Vector Machine Computational Biology Proteins
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Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

Scientific reports Feb 6, 2017
Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate ...
Genomics Proteins Genome Machine Learning Algorithms Genome-Wide Association Study
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Estimation of adsorption isotherm and mass transfer parameters in protein chromatography using artificial neural networks.

Journal of chromatography. A Jan 27, 2017
Mechanistic modeling has been repeatedly successfully applied in process development and control of protein chromatography. For each combination of adsorbate and adsorbent, the mechanistic models have to be calibrated. Some of the model parameters, s...
Calibration Proteins Models, Chemical Chromatography Neural Networks, Computer Adsorption
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Cancer subtype prediction from a pathway-level perspective by using a support vector machine based on integrated gene expression and protein network.

Computer methods and programs in biomedicine Jan 20, 2017
BACKGROUND AND OBJECTIVE: Distinguishing cancer subtypes is critical for selecting the appropriate treatment strategy. Bioinformatics approaches have gradually taken the place of clinical observations and pathological experiments. However, these appr...
Gene Expression Humans Algorithms Neoplasms Support Vector Machine Proteins
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A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

Proteins Jan 20, 2017
Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and th...
Protein Binding Computational Biology Cluster Analysis Proteins Benchmarking Protein Conformation Software Research Design Molecular Docking Simulation Machine Learning Structural Homology, Protein Binding Sites Thermodynamics Protein Interaction Mapping
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