AIMC Topic: Regulatory Sequences, Nucleic Acid

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iCREPCP: A deep learning-based web server for identifying base-resolution cis-regulatory elements within plant core promoters.

Plant communications Sep 28, 2022
Plants Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid Deep Learning
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EPI-Mind: Identifying Enhancer-Promoter Interactions Based on Transformer Mechanism.

Interdisciplinary sciences, computational life sciences May 28, 2022
MOTIVATION: Enhancer-Promoter Interactions (EPIs) is an essential step in the gene regulation process. However, the detection of EPIs by traditional wet experimental techniques is time-consuming and expensive. Thus, computational methods would be ver...
Gene Expression Regulation Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid Neural Networks, Computer Cell Line
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Deep learning modeling mA deposition reveals the importance of downstream cis-element sequences.

Nature communications May 17, 2022
The N-methyladenosine (mA) modification is deposited to nascent transcripts on chromatin, but its site-specificity mechanism is mostly unknown. Here we model the mA deposition to pre-mRNA by iM6A (intelligent mA), a deep learning method, demonstratin...
Deep Learning Methylation Base Sequence Regulatory Sequences, Nucleic Acid Codon, Terminator
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Chromatin interaction-aware gene regulatory modeling with graph attention networks.

Genome research Apr 8, 2022
Linking distal enhancers to genes and modeling their impact on target gene expression are longstanding unresolved problems in regulatory genomics and critical for interpreting noncoding genetic variation. Here, we present a new deep learning approach...
Gene Expression Regulation Binding Sites Regulatory Sequences, Nucleic Acid Chromatin Neural Networks, Computer Gene Regulatory Networks Transcription Factors
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DeepCAGE: Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility.

Genomics, proteomics & bioinformatics Mar 12, 2022
Although computational approaches have been complementing high-throughput biological experiments for the identification of functional regions in the human genome, it remains a great challenge to systematically decipher interactions between transcript...
Humans Genome, Human Binding Sites Regulatory Sequences, Nucleic Acid Deep Learning Protein Binding Transcription Factors Chromatin Chromatin Assembly and Disassembly
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CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.

PLoS computational biology Dec 13, 2021
Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from...
Chromatin Immunoprecipitation Sequencing Islets of Langerhans Monocytes DNA Regulatory Sequences, Nucleic Acid Humans Cells, Cultured Deep Learning Single-Cell Analysis Computational Biology
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Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram.

Nature methods Oct 28, 2021
Charting an organs' biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehe...
Chromatin Mice, Inbred C57BL Gene Expression Regulation Regulatory Sequences, Nucleic Acid RNA-Seq Mice Animals Male Gene Expression Profiling Transcriptome Deep Learning Software Single-Cell Analysis Brain Female
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ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.

PLoS computational biology Sep 7, 2021
Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understan...
Mutation Gene Expression Regulation Genes, Reporter Promoter Regions, Genetic Genome-Wide Association Study Humans Genome, Human Molecular Sequence Annotation Deep Learning Regulatory Sequences, Nucleic Acid Computational Biology Enhancer Elements, Genetic Transcription Initiation, Genetic Models, Genetic
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Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics.

Molecular diversity May 24, 2021
Convolutional neural networks (CNNs) have been used to extract information from various datasets of different dimensions. This approach has led to accurate interpretations in several subfields of biological research, like pharmacogenomics, addressing...
Precision Medicine Pharmacogenetics Polymorphism, Single Nucleotide Artificial Intelligence Data Analysis RNA Binding Sites Regulatory Sequences, Nucleic Acid Drug Development DNA Drug Interactions Neural Networks, Computer
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Deep learning-based enhancement of epigenomics data with AtacWorks.

Nature communications Mar 8, 2021
ATAC-seq is a widely-applied assay used to measure genome-wide chromatin accessibility; however, its ability to detect active regulatory regions can depend on the depth of sequencing coverage and the signal-to-noise ratio. Here we introduce AtacWorks...
Epigenomics Animals Humans Leukocytes Chromatin Regulatory Sequences, Nucleic Acid Brain Deep Learning Chromatin Immunoprecipitation Sequencing Mice
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