AI Medical Compendium Topic

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Epigenesis, Genetic

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Integrated epigenomic exposure signature discovery.

Epigenomics
The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Here we developed and implemented a machine learning algorithm, the exposure signature discove...

Determinants of Chromatin Organization in Aging and Cancer-Emerging Opportunities for Epigenetic Therapies and AI Technology.

Genes
This review article critically examines the pivotal role of chromatin organization in gene regulation, cellular differentiation, disease progression and aging. It explores the dynamic between the euchromatin and heterochromatin, coded by a complex ar...

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.

Translational psychiatry
Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention ha...

Machine Learning-Assisted Direct RNA Sequencing with Epigenetic RNA Modification Detection via Quantum Tunneling.

Analytical chemistry
RNA sequence information holds immense potential as a drug target for diagnosing various RNA-mediated diseases and viral/bacterial infections. Massively parallel complementary DNA (c-DNA) sequencing helps but results in a loss of valuable information...

Effective training of nanopore callers for epigenetic marks with limited labelled data.

Open biology
Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at detecting base modifications in DNA such as 5-methylcytosine (5mC) and N6-methyladenine (6mA). These ML-based nanopore callers have typically been tra...

A miRNA-based epigenetic molecular clock for biological skin-age prediction.

Archives of dermatological research
Skin aging is one of the visible characteristics of the aging process in humans. In recent years, different biological clocks have been generated based on protein or epigenetic markers, but few have focused on biological age in the skin. Arrest the a...

Deep learning with a small dataset predicts chromatin remodelling contribution to winter dormancy of apple axillary buds.

Tree physiology
Epigenetic changes serve as a cellular memory for cumulative cold recognition in both herbaceous and tree species, including bud dormancy. However, most studies have discussed predicted chromatin structure with respect to histone marks. In the presen...

Current genomic deep learning models display decreased performance in cell type-specific accessible regions.

Genome biology
BACKGROUND: A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), whi...

Deep learning meets histones at the replication fork.

Cell
Epigenetic inheritance of heterochromatin requires transfer of parental H3-H4 tetramers to both daughter duplexes during replication. Three recent papers exploit yeast genetics coupled to inheritance assays and AlphaFold2-multimer predictions coupled...

Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model.

Bioinformatics (Oxford, England)
MOTIVATION: 5-Hydroxymethylcytosine (5hmC), a crucial epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Despite its importance, predicting ...