AIMC Topic: Binding Sites

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Recurrent Neural Network for Predicting Transcription Factor Binding Sites.

Scientific reports Oct 15, 2018
It is well known that DNA sequence contains a certain amount of transcription factors (TF) binding sites, and only part of them are identified through biological experiments. However, these experiments are expensive and time-consuming. To overcome th...
Computational Biology Transcription Factors Databases, Genetic Binding Sites Neural Networks, Computer Algorithms Protein Binding
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Sequential Integration of Fuzzy Clustering and Expectation Maximization for Transcription Factor Binding Site Identification.

Journal of computational biology : a journal of computational molecular cell biology Aug 22, 2018
The identification of transcription factor binding sites (TFBSs) is a problem for which computational methods offer great hope. Thus far, the expectation maximization (EM) technique has been successfully utilized in finding TFBSs in DNA sequences, bu...
Protein Binding Computational Biology Transcription Factors Sequence Analysis, DNA Humans Algorithms Chromatin Immunoprecipitation Fuzzy Logic Cluster Analysis Binding Sites Nucleotide Motifs
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Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges.

Journal of computer-aided molecular design Aug 16, 2018
Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affin...
Molecular Docking Simulation Computer-Aided Design Drug Design Receptors, Cytoplasmic and Nuclear Binding Sites Thermodynamics Cathepsins Protein Kinases Ligands Crystallography, X-Ray Protein Conformation Deep Learning Protein Binding Databases, Protein
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Weakly-Supervised Convolutional Neural Network Architecture for Predicting Protein-DNA Binding.

IEEE/ACM transactions on computational biology and bioinformatics Aug 7, 2018
Although convolutional neural networks (CNN) have outperformed conventional methods in predicting the sequence specificities of protein-DNA binding in recent years, they do not take full advantage of the intrinsic weakly-supervised information of DNA...
Transcription Factors DNA DNA-Binding Proteins Supervised Machine Learning Protein Binding Mice Computational Biology Neural Networks, Computer Algorithms Binding Sites Animals
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EL_LSTM: Prediction of DNA-Binding Residue from Protein Sequence by Combining Long Short-Term Memory and Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics Jul 23, 2018
Most past works for DNA-binding residue prediction did not consider the relationships between residues. In this paper, we propose a novel approach for DNA-binding residue prediction, referred to as EL_LSTM, which includes two main components. The fir...
DNA DNA-Binding Proteins Binding Sites Machine Learning Algorithms Computational Biology Databases, Protein
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miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts.

PLoS computational biology Jul 13, 2018
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to partially complementary regions within the 3'UTR of their target genes. Computational methods play an important role in target prediction and assume that the miR...
Humans Neural Networks, Computer Computer Simulation Reproducibility of Results Gene Targeting Datasets as Topic 3' Untranslated Regions Gene Expression Regulation Deep Learning Binding Sites Thermodynamics RNA, Messenger MicroRNAs
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Convolutional neural network scoring and minimization in the D3R 2017 community challenge.

Journal of computer-aided molecular design Jul 10, 2018
We assess the ability of our convolutional neural network (CNN)-based scoring functions to perform several common tasks in the domain of drug discovery. These include correctly identifying ligand poses near and far from the true binding mode when giv...
Binding Sites Cathepsins Structure-Activity Relationship Ligands Protein Conformation Neural Networks, Computer Algorithms Molecular Docking Simulation Drug Discovery Protein Binding Databases, Protein
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Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks.

BMC genomics Jul 3, 2018
BACKGROUND: RNA regulation is significantly dependent on its binding protein partner, known as the RNA-binding proteins (RBPs). Unfortunately, the binding preferences for most RBPs are still not well characterized. Interdependencies between sequence ...
Nucleotide Motifs User-Computer Interface Protein Binding Computational Biology Neural Networks, Computer RNA-Binding Proteins Algorithms RNA Nucleic Acid Conformation Binding Sites
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Computational design of thermostabilizing point mutations for G protein-coupled receptors.

eLife Jun 21, 2018
Engineering of GPCR constructs with improved thermostability is a key for successful structural and biochemical studies of this transmembrane protein family, targeted by 40% of all therapeutic drugs. Here we introduce a comprehensive computational ap...
Amino Acid Sequence Point Mutation Protein Stability Receptor, Serotonin, 5-HT2C Serotonin 5-HT2 Receptor Agonists Humans Crystallography, X-Ray Serotonin 5-HT2 Receptor Antagonists Binding Sites Sequence Homology, Amino Acid Machine Learning Models, Molecular Protein Engineering Animals Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Gene Expression Protein Binding Thermodynamics Protein Conformation, beta-Strand Kinetics Sequence Alignment
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Development of machine learning models to predict inhibition of 3-dehydroquinate dehydratase.

Chemical biology & drug design May 18, 2018
In this study, we describe the development of new machine learning models to predict inhibition of the enzyme 3-dehydroquinate dehydratase (DHQD). This enzyme is the third step of the shikimate pathway and is responsible for the synthesis of chorisma...
ROC Curve Protein Structure, Tertiary Humans Area Under Curve Hydro-Lyases Machine Learning Static Electricity Shikimic Acid Molecular Docking Simulation Binding Sites
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