AIMC Topic: Epigenomics

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Biomarkers of aging - current state of knowledge.

Casopis lekaru ceskych
Aging is a process of gradual decline in the functional capacity of the human body that leads to a significant increase in the risk of death over time. Although it is a process universal to all animals, its rate is not the same. Biomarkers of aging a...

Towards multi-omics characterization of tumor heterogeneity: a comprehensive review of statistical and machine learning approaches.

Briefings in bioinformatics
The multi-omics molecular characterization of cancer opened a new horizon for our understanding of cancer biology and therapeutic strategies. However, a tumor biopsy comprises diverse types of cells limited not only to cancerous cells but also to tum...

Artificial Intelligence for Epigenetics: Towards Personalized Medicine.

Current medicinal chemistry
Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function, not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mec...

Graph convolutional networks for epigenetic state prediction using both sequence and 3D genome data.

Bioinformatics (Oxford, England)
MOTIVATION: Predictive models of DNA chromatin profile (i.e. epigenetic state), such as transcription factor binding, are essential for understanding regulatory processes and developing gene therapies. It is known that the 3D genome, or spatial struc...

Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning-based neural network.

GigaScience
BACKGROUND: Gene expression plays a key intermediate role in linking molecular features at the DNA level and phenotype. However, owing to various limitations in experiments, the RNA-seq data are missing in many samples while there exist high-quality ...

Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Interactions among cis-regulatory elements such as enhancers and promoters are main driving forces shaping context-specific chromatin structure and gene expression. Although there have been computational methods for predicting gene expres...

Quantitative Modelling of the Waddington Epigenetic Landscape.

Methods in molecular biology (Clifton, N.J.)
C.H. Waddington introduced the epigenetic landscape as a metaphor to represent cellular decision-making during development. Like a population of balls rolling down a rough hillside, developing cells follow specific trajectories (valleys) and eventual...

Machine Learning Methods in Precision Medicine Targeting Epigenetic Diseases.

Current pharmaceutical design
BACKGROUND: On a tide of big data, machine learning is coming to its day. Referring to huge amounts of epigenetic data coming from biological experiments and clinic, machine learning can help in detecting epigenetic features in genome, finding correl...

Epigenomic annotation-based interpretation of genomic data: from enrichment analysis to machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: One of the goals of functional genomics is to understand the regulatory implications of experimentally obtained genomic regions of interest (ROIs). Most sequencing technologies now generate ROIs distributed across the whole genome. The in...