AIMC Topic: Binding Sites

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DeepMotifSyn: a deep learning approach to synthesize heterodimeric DNA motifs.

Briefings in bioinformatics Jan 17, 2022
The cooperativity of transcription factors (TFs) is a widespread phenomenon in the gene regulation system. However, the interaction patterns between TF binding motifs remain elusive. The recent high-throughput assays, CAP-SELEX, have identified over ...
Protein Binding Transcription Factors Binding Sites Nucleotide Motifs Humans Deep Learning
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Epitome: predicting epigenetic events in novel cell types with multi-cell deep ensemble learning.

Nucleic acids research Nov 8, 2021
The accumulation of large epigenomics data consortiums provides us with the opportunity to extrapolate existing knowledge to new cell types and conditions. We propose Epitome, a deep neural network that learns similarities of chromatin accessibility ...
Epigenesis, Genetic Transcription Factors Cell Communication Genome, Human Machine Learning Software Protein Binding Atlases as Topic Chromatin Chromatin Immunoprecipitation Eukaryotic Cells Histones Binding Sites Cell Lineage Humans Neural Networks, Computer
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Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Briefings in bioinformatics Nov 5, 2021
Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is ...
RNA-Binding Proteins Databases, Genetic Base Sequence Binding Sites RNA, Circular Deep Learning ROC Curve Computational Biology Algorithms Reproducibility of Results
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High-resolution transcription factor binding sites prediction improved performance and interpretability by deep learning method.

Briefings in bioinformatics Nov 5, 2021
Transcription factors (TFs) are essential proteins in regulating the spatiotemporal expression of genes. It is crucial to infer the potential transcription factor binding sites (TFBSs) with high resolution to promote biology and realize precision med...
Transcription Factors Deep Learning Binding Sites Protein Binding Chromatin Immunoprecipitation Computational Biology
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Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution.

Briefings in bioinformatics Nov 5, 2021
Major histocompatibility complex (MHC) possesses important research value in the treatment of complex human diseases. A plethora of computational tools has been developed to predict MHC class I binders. Here, we comprehensively reviewed 27 up-to-date...
Epitopes Histocompatibility Antigens Class I Amino Acid Sequence Binding Sites Protein Binding Computational Biology Carrier Proteins Neural Networks, Computer Web Browser Deep Learning Machine Learning Databases, Factual ROC Curve Software Reproducibility of Results
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Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2.

Proceedings of the National Academy of Sciences of the United States of America Oct 19, 2021
The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 ha...
Binding Sites Neural Networks, Computer SARS-CoV-2 Spike Glycoprotein, Coronavirus Molecular Dynamics Simulation Humans Angiotensin-Converting Enzyme 2 Amino Acid Substitution Host-Pathogen Interactions
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SAResNet: self-attention residual network for predicting DNA-protein binding.

Briefings in bioinformatics Sep 2, 2021
Knowledge of the specificity of DNA-protein binding is crucial for understanding the mechanisms of gene expression, regulation and gene therapy. In recent years, deep-learning-based methods for predicting DNA-protein binding from sequence data have a...
Computational Biology Reproducibility of Results Humans DNA-Binding Proteins DNA Neural Networks, Computer Deep Learning Binding Sites Internet Algorithms Protein Binding
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Explainability in transformer models for functional genomics.

Briefings in bioinformatics Sep 2, 2021
The effectiveness of deep learning methods can be largely attributed to the automated extraction of relevant features from raw data. In the field of functional genomics, this generally concerns the automatic selection of relevant nucleotide motifs fr...
Base Sequence Promoter Regions, Genetic Binding Sites Deep Learning Genome, Bacterial DNA, Bacterial Transcription Initiation Site Genomics Transcription Factors Escherichia coli
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DeepDTAF: a deep learning method to predict protein-ligand binding affinity.

Briefings in bioinformatics Sep 2, 2021
Biomolecular recognition between ligand and protein plays an essential role in drug discovery and development. However, it is extremely time and resource consuming to determine the protein-ligand binding affinity by experiments. At present, many comp...
Protein Conformation, alpha-Helical Data Accuracy Hydrogen Bonding Drug Discovery Binding Sites Deep Learning Models, Molecular Protein Binding Amino Acid Sequence Software Proteins Ligands Reproducibility of Results
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Accurate prediction of inter-protein residue-residue contacts for homo-oligomeric protein complexes.

Briefings in bioinformatics Sep 2, 2021
Protein-protein interactions play a fundamental role in all cellular processes. Therefore, determining the structure of protein-protein complexes is crucial to understand their molecular mechanisms and develop drugs targeting the protein-protein inte...
Humans Software Protein Interaction Domains and Motifs Protein Binding Molecular Docking Simulation Datasets as Topic Protein Conformation, alpha-Helical Proteins Protein Conformation, beta-Strand Deep Learning Binding Sites Protein Multimerization
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