AIMC Topic: Chromatin

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Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.

Cell genomics Feb 27, 2025
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how co...
Humans Animals Deep Learning Binding Sites Chromatin Nucleosomes SOX9 Transcription Factor Protein Binding Mice Transcription Factors
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A multi-modal transformer for cell type-agnostic regulatory predictions.

Cell genomics Jan 29, 2025
Sequence-based deep learning models have emerged as powerful tools for deciphering the cis-regulatory grammar of the human genome but cannot generalize to unobserved cellular contexts. Here, we present EpiBERT, a multi-modal transformer that learns g...
Deep Learning Genomics Genome, Human Quantitative Trait Loci Chromatin Humans Neural Networks, Computer
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Fluo-Cast-Bright: a deep learning pipeline for the non-invasive prediction of chromatin structure and developmental potential in live oocytes.

Communications biology Jan 29, 2025
In mammalian oocytes, large-scale chromatin organization regulates transcription, nuclear architecture, and maintenance of chromosome stability in preparation for meiosis onset. Pre-ovulatory oocytes with distinct chromatin configurations exhibit pro...
Mice Oocytes Meiosis Animals Gene Expression Profiling Deep Learning Chromatin Female
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The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models.

PLoS computational biology Jan 10, 2025
Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they...
Genomics Computational Biology Models, Genetic Natural Language Processing Humans Deep Learning Introns Chromatin
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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...
Mice Computational Biology Regulatory Sequences, Nucleic Acid Transcription Factors Chromatin Chromatin Immunoprecipitation Sequencing DNA Gene Expression Regulation Nucleic Acid Conformation Machine Learning Animals Humans Single-Cell Analysis
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Identification, characterization, and design of plant genome sequences using deep learning.

The Plant journal : for cell and molecular biology Dec 12, 2024
Due to its excellent performance in processing large amounts of data and capturing complex non-linear relationships, deep learning has been widely applied in many fields of plant biology. Here we first review the application of deep learning in analy...
Chromatin Genomics Plants Genome, Plant Algorithms Deep Learning
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Predicting cell type-specific epigenomic profiles accounting for distal genetic effects.

Nature communications Nov 16, 2024
Understanding how genetic variants affect the epigenome is key to interpreting GWAS, yet profiling these effects across the non-coding genome remains challenging due to experimental scalability. This necessitates accurate computational models. Existi...
Models, Genetic Polymorphism, Single Nucleotide DNA Epigenome Humans Epigenesis, Genetic Quantitative Trait Loci Epigenomics Deep Learning Chromatin Genome-Wide Association Study
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Comprehensive multi-omics analysis identifies chromatin regulator-related signatures and TFF1 as a therapeutic target in lung adenocarcinoma through a 429-combination machine learning approach.

Frontiers in immunology Oct 30, 2024
INTRODUCTION: Lung cancer is a leading cause of cancer-related deaths, with its incidence continuing to rise. Chromatin remodeling, a crucial process in gene expression regulation, plays a significant role in the development and progression of malign...
Adenocarcinoma of Lung Female Cell Proliferation Chromatin Humans Tumor Microenvironment Apoptosis Trefoil Factor-1 Biomarkers, Tumor Xenograft Model Antitumor Assays Animals Machine Learning Mice Cell Line, Tumor Prognosis Multiomics Lung Neoplasms Gene Expression Regulation, Neoplastic
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Convolutional neural network-based regression analysis to predict subnuclear chromatin organization from two-dimensional optical scattering signals.

Journal of biomedical optics Aug 28, 2024
SIGNIFICANCE: Azimuth-resolved optical scattering signals obtained from cell nuclei are sensitive to changes in their internal refractive index profile. These two-dimensional signals can therefore offer significant insights into chromatin organizatio...
Algorithms Scattering, Radiation Refractometry Regression Analysis Chromatin Humans Cell Nucleus Neural Networks, Computer Machine Learning
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Machine learning approaches to detect hepatocyte chromatin alterations from iron oxide nanoparticle exposure.

Scientific reports Aug 23, 2024
This study focuses on developing machine learning models to detect subtle alterations in hepatocyte chromatin organization due to Iron (II, III) oxide nanoparticle exposure, hypothesizing that exposure will significantly alter chromatin texture. A to...
Mice Liver Magnetic Iron Oxide Nanoparticles Hepatocytes Ferric Compounds Chromatin Machine Learning Animals Male
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