AIMC Topic: Proteins

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Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

Journal of theoretical biology Apr 2, 2015
As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimen...
Proteins Amino Acids Internet Computational Biology Support Vector Machine Protein Processing, Post-Translational Binding Sites Succinates Molecular Sequence Data Supervised Machine Learning Amino Acid Sequence Lysine Artificial Intelligence Algorithms Computer Simulation Reproducibility of Results
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Exploring the relationship between hub proteins and drug targets based on GO and intrinsic disorder.

Computational biology and chemistry Mar 23, 2015
Protein-protein interactions (PPIs) play essential roles in many biological processes. In protein-protein interaction networks, hubs involve in numbers of PPIs and may constitute an important source of drug targets. The intrinsic disorder proteins (I...
Humans Drug Discovery Gene Ontology Proteins Protein Interaction Mapping Protein Interaction Maps Databases, Protein Computational Biology Molecular Targeted Therapy Support Vector Machine
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Clustering molecular dynamics trajectories for optimizing docking experiments.

Computational intelligence and neuroscience Mar 22, 2015
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the f...
Algorithms Artificial Intelligence Cluster Analysis Software Proteins Molecular Dynamics Simulation Ligands
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BgN-Score and BsN-Score: bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes.

BMC bioinformatics Feb 23, 2015
BACKGROUND: Accurately predicting the binding affinities of large sets of protein-ligand complexes is a key challenge in computational biomolecular science, with applications in drug discovery, chemical biology, and structural biology. Since a scorin...
Proteins Ligands Binding Sites Protein Binding Computational Biology Humans Models, Statistical Neural Networks, Computer Artificial Intelligence Algorithms
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Bioinformatics approaches for the functional interpretation of protein lists: from ontology term enrichment to network analysis.

Proteomics Feb 20, 2015
The main result of a great deal of the published proteomics studies is a list of identified proteins, which then needs to be interpreted in relation to the research question and existing knowledge. In the early days of proteomics this interpretation ...
Biological Ontologies Computational Biology Proteins Databases, Protein
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Machine learning in computational docking.

Artificial intelligence in medicine Feb 16, 2015
OBJECTIVE: The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has...
Ligands Protein Conformation Protein Binding Computational Biology Proteins Databases, Protein Data Interpretation, Statistical Quantum Theory Humans Machine Learning
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Computationally predicting protein-RNA interactions using only positive and unlabeled examples.

Journal of bioinformatics and computational biology Feb 8, 2015
Protein-RNA interactions (PRIs) are considerably important in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulations of gene expression to the active defense of host against virus. With the development...
Bone Substitutes Drosophila melanogaster Caenorhabditis elegans Protein Interaction Mapping Support Vector Machine Humans Escherichia coli Animals Databases, Protein Proteins Mice RNA Saccharomyces cerevisiae
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BagReg: Protein inference through machine learning.

Computational biology and chemistry Feb 7, 2015
Protein inference from the identified peptides is of primary importance in the shotgun proteomics. The target of protein inference is to identify whether each candidate protein is truly present in the sample. To date, many computational methods have ...
Computational Biology Proteins Databases, Protein Machine Learning
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Types and effects of protein variations.

Human genetics Jan 24, 2015
Variations in proteins have very large number of diverse effects affecting sequence, structure, stability, interactions, activity, abundance and other properties. Although protein-coding exons cover just over 1 % of the human genome they harbor an di...
Protein Folding Protein Structure, Quaternary Genetic Variation Gene Ontology Protein Structure, Secondary Models, Molecular Molecular Dynamics Simulation Amino Acid Sequence Proteins Humans Databases, Protein Animals Structure-Activity Relationship Protein Processing, Post-Translational
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More challenges for machine-learning protein interactions.

Bioinformatics (Oxford, England) Jan 12, 2015
MOTIVATION: Machine learning may be the most popular computational tool in molecular biology. Providing sustained performance estimates is challenging. The standard cross-validation protocols usually fail in biology. Park and Marcotte found that even...
Humans Artificial Intelligence Computational Biology Proteins Protein Interaction Mapping Saccharomyces cerevisiae Proteins Sequence Analysis, Protein
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