AIMC Topic: Chromatin

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IChrom-Deep: An Attention-Based Deep Learning Model for Identifying Chromatin Interactions.

IEEE journal of biomedical and health informatics Sep 6, 2023
Identification of chromatin interactions is crucial for advancing our knowledge of gene regulation. However, due to the limitations of high-throughput experimental techniques, there is an urgent need to develop computational methods for predicting ch...
Humans Gene Expression Regulation Chromatin Deep Learning Genomics
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Early detection of lung cancer using artificial intelligence-enhanced optical nanosensing of chromatin alterations in field carcinogenesis.

Scientific reports Aug 22, 2023
Supranucleosomal chromatin structure, including chromatin domain conformation, is involved in the regulation of gene expression and its dysregulation has been associated with carcinogenesis. Prior studies have shown that cells in the buccal mucosa ca...
Lung Neoplasms Early Detection of Cancer Humans Artificial Intelligence Carcinogenesis Chromatin
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A deep learning method for replicate-based analysis of chromosome conformation contacts using Siamese neural networks.

Nature communications Aug 17, 2023
The organisation of the genome in nuclear space is an important frontier of biology. Chromosome conformation capture methods such as Hi-C and Micro-C produce genome-wide chromatin contact maps that provide rich data containing quantitative and qualit...
Chromatin Deep Learning Molecular Conformation Neural Networks, Computer
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Interpretable single-cell transcription factor prediction based on deep learning with attention mechanism.

Computational biology and chemistry Aug 7, 2023
Predicting the transcription factor binding site (TFBS) in the whole genome range is essential in exploring the rule of gene transcription control. Although many deep learning methods to predict TFBS have been proposed, predicting TFBS using single-c...
Transcription Factors Neural Networks, Computer Gene Expression Regulation Deep Learning Chromatin
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DeepSATA: A Deep Learning-Based Sequence Analyzer Incorporating the Transcription Factor Binding Affinity to Dissect the Effects of Non-Coding Genetic Variants.

International journal of molecular sciences Jul 27, 2023
Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic variants, and uncover mechanisms behind complex traits. However, these tools primarily rely on human or ...
DNA Chromatin Chickens Transcription Factors Swine Deep Learning Cattle Mice Humans Animals
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ExplaiNN: interpretable and transparent neural networks for genomics.

Genome biology Jun 27, 2023
Deep learning models such as convolutional neural networks (CNNs) excel in genomic tasks but lack interpretability. We introduce ExplaiNN, which combines the expressiveness of CNNs with the interpretability of linear models. ExplaiNN can predict TF b...
Chromatin Neural Networks, Computer Protein Binding Genomics
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Transfer learning enables predictions in network biology.

Nature May 31, 2023
Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recen...
Chromatin Datasets as Topic Cardiomyopathies Single-Cell Gene Expression Analysis Biology Neural Networks, Computer Machine Learning Humans
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Genomic benchmarks: a collection of datasets for genomic sequence classification.

BMC genomic data May 1, 2023
BACKGROUND: Recently, deep neural networks have been successfully applied in many biological fields. In 2020, a deep learning model AlphaFold won the protein folding competition with predicted structures within the error tolerance of experimental met...
Humans Neural Networks, Computer Machine Learning Chromatin Genomics Animals Benchmarking Mice
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Efficient Generation of Paired Single-Cell Multiomics Profiles by Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 28, 2023
Recent advances in single-cell sequencing technology have made it possible to measure multiple paired omics simultaneously in a single cell such as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-nucleus chromatin...
Membrane Proteins RNA Humans Deep Learning Chromatin Multiomics
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A Unified Deep Learning Framework for Single-Cell ATAC-Seq Analysis Based on ProdDep Transformer Encoder.

International journal of molecular sciences Mar 1, 2023
Recent advances in single-cell sequencing assays for the transposase-accessibility chromatin (scATAC-seq) technique have provided cell-specific chromatin accessibility landscapes of cis-regulatory elements, providing deeper insights into cellular sta...
Gene Expression Regulation Single-Cell Analysis Deep Learning Chromatin Transcription Factors Chromatin Immunoprecipitation Sequencing
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