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Chromatin

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Early detection of lung cancer using artificial intelligence-enhanced optical nanosensing of chromatin alterations in field carcinogenesis.

Scientific reports
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...

Interpretable single-cell transcription factor prediction based on deep learning with attention mechanism.

Computational biology and chemistry
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...

A deep learning method for replicate-based analysis of chromosome conformation contacts using Siamese neural networks.

Nature communications
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...

MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites.

Genome biology
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...

ORI-Explorer: a unified cell-specific tool for origin of replication sites prediction by feature fusion.

Bioinformatics (Oxford, England)
MOTIVATION: The origins of replication sites (ORIs) are precise regions inside the DNA sequence where the replication process begins. These locations are critical for preserving the genome's integrity during cell division and guaranteeing the faithfu...

A Comprehensive Evaluation of Generalizability of Deep Learning-Based Hi-C Resolution Improvement Methods.

Genes
Hi-C is a widely used technique to study the 3D organization of the genome. Due to its high sequencing cost, most of the generated datasets are of a coarse resolution, which makes it impractical to study finer chromatin features such as Topologically...

Machine learning and experimental screening of chromatin regulator signatures and potential drugs in hepatitis B related hepatocellular carcinoma.

Journal of biomolecular structure & dynamics
Many evidences have confirmed that chromatin regulator factors (CRs) are involved in the progression of cancer, but its potential mechanism of affecting hepatitis B related hepatocellular carcinoma still needs to be studied. Our study detected the CR...

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

Nature
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...

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Briefings in bioinformatics
Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell label...

A systematic analyses of different bioinformatics pipelines for genomic data and its impact on deep learning models for chromatin loop prediction.

Briefings in functional genomics
Genomic data analysis has witnessed a surge in complexity and volume, primarily driven by the advent of high-throughput technologies. In particular, studying chromatin loops and structures has become pivotal in understanding gene regulation and genom...