AIMC Topic: Chromatin

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scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Nucleic acids research Jan 7, 2022
Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populati...
Genetic Heterogeneity Gene Expression Regulation Promoter Regions, Genetic Organ Specificity Humans Databases, Genetic Software Unsupervised Machine Learning Gene Regulatory Networks Internet Mice Animals Single-Cell Analysis Enhancer Elements, Genetic Chromatin Consensus Sequence Eukaryotic Cells Drosophila melanogaster Molecular Sequence Annotation Cell Lineage
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Convolutional Neural Networks for Classifying Chromatin Morphology in Live-Cell Imaging.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Chromatin is highly structured, and changes in its organization are essential in many cellular processes, including cell division. Recently, advances in machine learning have enabled researchers to automatically classify chromatin morphology in fluor...
Chromatin Neural Networks, Computer Machine Learning Microscopy, Fluorescence
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TempoMAGE: a deep learning framework that exploits the causal dependency between time-series data to predict histone marks in open chromatin regions at time-points with missing ChIP-seq datasets.

Bioinformatics (Oxford, England) Dec 7, 2021
MOTIVATION: Identifying histone tail modifications using ChIP-seq is commonly used in time-series experiments in development and disease. These assays, however, cover specific time-points leaving intermediate or early stages with missing information....
Deep Learning Regulatory Sequences, Nucleic Acid Chromatin Histone Code Chromatin Immunoprecipitation Sequencing
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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 ...
Cell Communication Genome, Human Histones Binding Sites Protein Binding Epigenesis, Genetic Transcription Factors Chromatin Immunoprecipitation Eukaryotic Cells Cell Lineage Atlases as Topic Chromatin Machine Learning Software Humans Neural Networks, Computer
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iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network.

Briefings in bioinformatics Sep 2, 2021
DNase I hypersensitive site (DHS) refers to the hypersensitive region of chromatin for the DNase I enzyme. It is an important part of the noncoding region and contains a variety of regulatory elements, such as promoter, enhancer, and transcription fa...
Oryza Genetic Loci Datasets as Topic Enhancer Elements, Genetic Arabidopsis Promoter Regions, Genetic Transcription, Genetic Transcription Factors DNA Internet Software Deep Learning Protein Binding Humans Chromatin Deoxyribonuclease I
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A sequence-based deep learning approach to predict CTCF-mediated chromatin loop.

Briefings in bioinformatics Sep 2, 2021
Three-dimensional (3D) architecture of the chromosomes is of crucial importance for transcription regulation and DNA replication. Various high-throughput chromosome conformation capture-based methods have revealed that CTCF-mediated chromatin loops a...
Gene Expression Regulation Genome, Human Molecular Conformation Chromatin CCCTC-Binding Factor K562 Cells Nucleotide Motifs Neural Networks, Computer Software MCF-7 Cells Datasets as Topic Humans
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Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.

Briefings in bioinformatics Sep 2, 2021
The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as h...
Genome, Human Chromatin Chromatin Assembly and Disassembly Unsupervised Machine Learning Supervised Machine Learning Humans Base Sequence Epigenesis, Genetic Sequence Analysis, DNA
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DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops.

Briefings in bioinformatics Jul 20, 2021
The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction between active enhancers and promoter-proximal elements. YY1-mediated enhancer-promoter interaction is the general feature of mammalian gene control. Recently, some comput...
Chromatin YY1 Transcription Factor Databases, Factual Models, Biological Deep Learning Humans HCT116 Cells K562 Cells
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Deep-joint-learning analysis model of single cell transcriptome and open chromatin accessibility data.

Briefings in bioinformatics Jul 20, 2021
Simultaneous profiling transcriptomic and chromatin accessibility information in the same individual cells offers an unprecedented resolution to understand cell states. However, computationally effective methods for the integration of these inherent ...
Humans Databases, Factual Models, Biological Transcriptome Chromatin K562 Cells Deep Learning Single-Cell Analysis
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Interpretation of deep learning in genomics and epigenomics.

Briefings in bioinformatics May 20, 2021
Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies tow...
Chromatin Genomics Neural Networks, Computer DNA Computational Biology Deep Learning Gene Expression Epigenesis, Genetic Protein Binding RNA
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