AIMC Topic: Chromatin

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Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo.

Nature Dec 12, 2023
Enhancers control gene expression and have crucial roles in development and homeostasis. However, the targeted de novo design of enhancers with tissue-specific activities has remained challenging. Here we combine deep learning and transfer learning t...
Datasets as Topic Synthetic Biology Embryo, Nonmammalian Deep Learning Single-Cell Analysis Enhancer Elements, Genetic Reproducibility of Results Chromatin Neural Networks, Computer Animals Transposases Organ Specificity Drosophila melanogaster
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MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites.

Genome biology Oct 16, 2023
Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of noncoding variants in this unusual genome of malaria parasites remain elusive. We developed a sequence-based, ab initio deep learning framework, MalariaSE...
Plasmodium falciparum Malaria Animals Deep Learning Protozoan Proteins Drug Resistance Chromatin Antimalarials Malaria, Falciparum Humans Parasites
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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...
Gene Expression Regulation Deep Learning Genomics Humans Chromatin
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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 Chromatin Carcinogenesis Humans Artificial Intelligence
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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...
Neural Networks, Computer Deep Learning Chromatin Molecular Conformation
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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...
Gene Expression Regulation Chromatin Deep Learning Transcription Factors Neural Networks, Computer
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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 ...
Swine Deep Learning Mice Chickens Cattle Humans Animals Chromatin Transcription Factors DNA
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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...
Genomics Chromatin Neural Networks, Computer Protein Binding
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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...
Biology Machine Learning Datasets as Topic Single-Cell Gene Expression Analysis Chromatin Humans Cardiomyopathies Neural Networks, Computer
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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...
Animals Mice Neural Networks, Computer Machine Learning Chromatin Genomics Benchmarking Humans
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