AIMC Topic: Regulatory Sequences, Nucleic Acid

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ChromatinHD connects single-cell DNA accessibility and conformation to gene expression through scale-adaptive machine learning.

Nature communications Jan 2, 2025
Gene regulation is inherently multiscale, but scale-adaptive machine learning methods that fully exploit this property in single-nucleus accessibility data are still lacking. Here, we develop ChromatinHD, a pair of scale-adaptive models that uses the...
Computational Biology Transcription Factors DNA Single-Cell Analysis Mice Regulatory Sequences, Nucleic Acid Machine Learning Chromatin Animals Chromatin Immunoprecipitation Sequencing Humans Gene Expression Regulation Nucleic Acid Conformation
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Interpreting cis-regulatory interactions from large-scale deep neural networks.

Nature genetics Sep 16, 2024
The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with orthogonal experimental data, providin...
Humans Neural Networks, Computer Animals Gene Expression Regulation Regulatory Sequences, Nucleic Acid Genomics Models, Genetic Deep Learning Gene Regulatory Networks
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Current genomic deep learning models display decreased performance in cell type-specific accessible regions.

Genome biology Aug 1, 2024
BACKGROUND: A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), whi...
Epigenesis, Genetic Models, Genetic Organ Specificity Deep Learning Genomics Regulatory Sequences, Nucleic Acid Chromatin Humans
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Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Journal of human genetics May 10, 2024
Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory el...
Gene Expression Regulation Base Sequence Regulatory Sequences, Nucleic Acid Transcription, Genetic Sequence Analysis, DNA Alleles Genomics Computational Biology Humans Machine Learning
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Deep learning the cis-regulatory code for gene expression in selected model plants.

Nature communications Apr 25, 2024
Elucidating the relationship between non-coding regulatory element sequences and gene expression is crucial for understanding gene regulation and genetic variation. We explored this link with the training of interpretable deep learning models predict...
Deep Learning Zea mays Gene Expression Regulation, Plant Arabidopsis Sorghum Species Specificity Regulatory Sequences, Nucleic Acid Solanum lycopersicum Genome, Plant Genetic Variation
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Hold out the genome: a roadmap to solving the cis-regulatory code.

Nature Dec 13, 2023
Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven ...
Transcription Factors DNA Regulatory Sequences, Nucleic Acid Genomics Machine Learning Models, Genetic
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CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms.

Genome biology Nov 23, 2023
Linking cis-regulatory sequences to target genes has been a long-standing challenge. In this study, we introduce CREaTor, an attention-based deep neural network designed to model cis-regulatory patterns for genomic elements up to 2 Mb from target gen...
Regulatory Sequences, Nucleic Acid Neural Networks, Computer
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NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America Apr 6, 2023
Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulator...
Neural Networks, Computer Nucleotide Motifs Algorithms Regulatory Sequences, Nucleic Acid Databases, Factual
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Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques.

BMC bioinformatics Dec 12, 2022
BACKGROUND: Cis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the spatio-temporal pattern of transcription; they are involved in a wide range of pivotal processes such as the development of specific cell-lines/tissues ...
Regulatory Sequences, Nucleic Acid Deep Learning Bayes Theorem Neural Networks, Computer Humans Machine Learning
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LangMoDHS: A deep learning language model for predicting DNase I hypersensitive sites in mouse genome.

Mathematical biosciences and engineering : MBE Oct 24, 2022
DNase I hypersensitive sites (DHSs) are a specific genomic region, which is critical to detect or understand cis-regulatory elements. Although there are many methods developed to detect DHSs, there is a big gap in practice. We presented a deep learni...
Regulatory Sequences, Nucleic Acid Deoxyribonuclease I Mice Genomics Animals Deep Learning
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