AIMC Topic: Epigenome

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Predicting the effect of CRISPR-Cas9-based epigenome editing.

eLife
Epigenetic regulation orchestrates mammalian transcription, but functional links between them remain elusive. To tackle this problem, we use epigenomic and transcriptomic data from 13 ENCODE cell types to train machine learning models to predict gene...

A ternary-code DNA methylome atlas of mouse tissues.

Genome biology
BACKGROUND: DNA cytosine modifications, including 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), are key epigenetic regulators with distinct functions. Dissecting the ternary code (C, 5mC, 5hmC) across tissues and cell types remains a cri...

Development and validation of peripheral blood DNA methylation signatures to predict response to biological therapy in adults with Crohn's disease (EPIC-CD): an epigenome-wide association study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Biological therapeutics are widely used in Crohn's disease, with evidence of efficacy from randomised trials and real-world experience. Primary non-response is a common, poorly understood problem. We aimed to assess blood methylation as a...

Epigenome-wide association study identifies a specific panel of DNA methylation signatures for antenatal and postpartum depressive symptoms.

Journal of affective disorders
Depression during pregnancy and postpartum poses significant risks to both maternal and child well-being. The underlying biological mechanisms are unclear, but epigenetic variation could be exploited as a plausible candidate for early detection. We i...

Genome-wide methylome modeling via generative AI incorporating long- and short-range interactions.

Science advances
Using millions of methylation segments, we developed DiffuCpG, a generative artificial intelligence (AI) diffusion model designed to solve the critical challenge of missing data in high-throughput methylation technologies. DiffuCpG goes beyond conven...

Predicting cell type-specific epigenomic profiles accounting for distal genetic effects.

Nature communications
Understanding how genetic variants affect the epigenome is key to interpreting GWAS, yet profiling these effects across the non-coding genome remains challenging due to experimental scalability. This necessitates accurate computational models. Existi...

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...

Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study.

Schizophrenia research
Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, del...

Latent Representation of the Human Pan-Celltype Epigenome Through a Deep Recurrent Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
The availability of thousands of assays of epigenetic activity necessitates compressed representations of these data sets that summarize the epigenetic landscape of the genome. Until recently, most such representations were cell type-specific, applyi...

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome.

Nature cancer
We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. Differential methylation among tumor entities relates to differences in ...