AIMC Topic: Chromatin

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DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data.

BMC bioinformatics Dec 12, 2022
BACKGROUND: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional an...
Promoter Regions, Genetic Chromatin Transcription Initiation Site Neural Networks, Computer Software
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iEnhancer-DCLA: using the original sequence to identify enhancers and their strength based on a deep learning framework.

BMC bioinformatics Nov 14, 2022
Enhancers are small regions of DNA that bind to proteins, which enhance the transcription of genes. The enhancer may be located upstream or downstream of the gene. It is not necessarily close to the gene to be acted on, because the entanglement struc...
Enhancer Elements, Genetic Chromatin Deep Learning DNA Neural Networks, Computer
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Multimodal Single-Cell Translation and Alignment with Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology Oct 14, 2022
Single-cell multi-omics technologies enable comprehensive interrogation of cellular regulation, yet most single-cell assays measure only one type of activity-such as transcription, chromatin accessibility, DNA methylation, or 3D chromatin architectur...
Chromatin Databases, Factual Supervised Machine Learning
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DLoopCaller: A deep learning approach for predicting genome-wide chromatin loops by integrating accessible chromatin landscapes.

PLoS computational biology Oct 7, 2022
In recent years, major advances have been made in various chromosome conformation capture technologies to further satisfy the needs of researchers for high-quality, high-resolution contact interactions. Discriminating the loops from genome-wide conta...
Transcription Factors Genome Chromatin Deep Learning Chromosomes
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Characterizing collaborative transcription regulation with a graph-based deep learning approach.

PLoS computational biology Jun 6, 2022
Human epigenome and transcription activities have been characterized by a number of sequence-based deep learning approaches which only utilize the DNA sequences. However, transcription factors interact with each other, and their collaborative regulat...
Chromatin Transcription Factors DNA Gene Expression Regulation Binding Sites Deep Learning Protein Binding Humans
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Machine Learning Methods for Exploring Sequence Determinants of 3D Genome Organization.

Journal of molecular biology Jun 2, 2022
In higher eukaryotic cells, chromosomes are folded inside the nucleus. Recent advances in whole-genome mapping technologies have revealed the multiscale features of 3D genome organization that are intertwined with fundamental genome functions. Howeve...
Imaging, Three-Dimensional Sequence Analysis, DNA Machine Learning Chromosomes Chromosome Mapping Chromatin Cell Nucleus Genome
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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...
Chromatin Gene Regulatory Networks Neural Networks, Computer Binding Sites Transcription Factors Gene Expression Regulation Regulatory Sequences, Nucleic Acid
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InsuLock: A Weakly Supervised Learning Approach for Accurate Insulator Prediction, and Variant Impact Quantification.

Genes Mar 30, 2022
Mapping chromatin insulator loops is crucial to investigating genome evolution, elucidating critical biological functions, and ultimately quantifying variant impact in diseases. However, chromatin conformation profiling assays are usually expensive, ...
Neural Networks, Computer CCCTC-Binding Factor Supervised Machine Learning Genome Chromatin
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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...
Deep Learning Protein Binding Chromatin Assembly and Disassembly Genome, Human Binding Sites Humans Regulatory Sequences, Nucleic Acid Transcription Factors Chromatin
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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...
Mice Chromatin Male Single-Cell Analysis Mice, Inbred C57BL Gene Expression Regulation Software Female RNA-Seq Transcriptome Gene Expression Profiling Regulatory Sequences, Nucleic Acid Brain Animals Deep Learning
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