AIMC Topic: Binding Sites

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DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants.

Nucleic acids research Jun 20, 2018
The complex system of gene expression is regulated by the cell type-specific binding of transcription factors (TFs) to regulatory elements. Identifying variants that disrupt TF binding and lead to human diseases remains a great challenge. To address ...
Humans Neural Networks, Computer Algorithms Gene Expression Regulation Binding Sites Regulatory Elements, Transcriptional Regulatory Sequences, Nucleic Acid Computational Biology Transcription Factors DNA DNA-Binding Proteins
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Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.

Bioinformatics (Oxford, England) May 1, 2018
MOTIVATION: Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally r...
Binding Sites Databases, Protein Models, Molecular RNA Machine Learning Protein Binding Computational Biology Proteins
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Survey of Computational Approaches for Prediction of DNA-Binding Residues on Protein Surfaces.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2018
The increasing number of protein structures with uncharacterized function necessitates the development of in silico prediction methods for functional annotations on proteins. In this chapter, different kinds of computational approaches are briefly in...
Machine Learning Molecular Docking Simulation DNA DNA-Binding Proteins Amino Acid Sequence Protein Conformation Protein Binding Computational Biology Databases, Protein Binding Sites Sequence Analysis, Protein
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Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

Combinatorial chemistry & high throughput screening Jan 1, 2018
AIM AND OBJECTIVE: Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug d...
Least-Squares Analysis Pharmaceutical Preparations Binding Sites Artificial Intelligence Humans Algorithms Drug Design Blood Proteins
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DeepSite: protein-binding site predictor using 3D-convolutional neural networks.

Bioinformatics (Oxford, England) Oct 1, 2017
MOTIVATION: An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years b...
Drug Design Proteins Protein Conformation Binding Sites Machine Learning Software Algorithms Neural Networks, Computer
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DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

Bioinformatics (Oxford, England) Oct 1, 2017
MOTIVATION: Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of ...
Binding Sites Nucleotide Motifs DNA-Binding Proteins Nucleic Acid Conformation Protein Array Analysis Software Protein Binding Genomics Transcription Factors Support Vector Machine Sequence Analysis, DNA DNA
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A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.

Nucleic acids research Aug 21, 2017
Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-s...
Humans Machine Learning High-Throughput Nucleotide Sequencing Gene Expression Regulation Computational Biology Base Sequence Algorithms Nucleotide Motifs Binding Sites RNA-Binding Proteins Reproducibility of Results Binding, Competitive Mutation Protein Binding 3' Untranslated Regions Internet
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NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions.

Nucleic acids research Jul 3, 2017
Peptides are extensively used to characterize functional or (linear) structural aspects of receptor-ligand interactions in biological systems, e.g. SH2, SH3, PDZ peptide-recognition domains, the MHC membrane receptors and enzymes such as kinases and ...
Sequence Alignment HLA-A1 Antigen HLA-B7 Antigen HLA-B8 Antigen HLA-DRB1 Chains Humans Ligands Cell Cycle Proteins Peptides Binding Sites Protein Binding Trans-Activators Databases, Protein Internet Basic Helix-Loop-Helix Leucine Zipper Transcription Factors Forkhead Transcription Factors Neural Networks, Computer Amino Acid Sequence Software Algorithms
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Supervised Machine Learning Methods Applied to Predict Ligand- Binding Affinity.

Current medicinal chemistry Jan 1, 2017
BACKGROUND: Calculation of ligand-binding affinity is an open problem in computational medicinal chemistry. The ability to computationally predict affinities has a beneficial impact in the early stages of drug development, since it allows a mathemati...
Binding Sites Humans Supervised Machine Learning Ligands
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Design of Knowledge Bases for Plant Gene Regulatory Networks.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary ...
Chromosome Mapping Web Browser Transcription Initiation Site Gene Expression Regulation, Plant Software Protein Binding Search Engine User-Computer Interface Computational Biology Database Management Systems Gene Regulatory Networks Transcription Factors Databases, Genetic Plants Knowledge Bases Binding Sites
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