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MRCNN: a deep learning model for regression of genome-wide DNA methylation (Q64075175)

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scholarly article by Qi Tian et al published 4 April 2019 in BMC Genomics

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English	MRCNN: a deep learning model for regression of genome-wide DNA methylation	scholarly article by Qi Tian et al published 4 April 2019 in BMC Genomics

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scholarly article

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MRCNN: a deep learning model for regression of genome-wide DNA methylation (English)

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author name string

Qi Tian

1

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Jianxiao Zou

2

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Jianxiong Tang

3

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Yuan Fang

4

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Zhongli Yu

5

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Shicai Fan

6

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publication date

4 April 2019

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language of work or name

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20

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Suppl 2

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192

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copyright license

Creative Commons Attribution 4.0 International

1 April 2019

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April 2022 Public Data File from Crossref

copyright status

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Fitting a mixture model by expectation maximization to discover motifs in biopolymers

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Site-selective in vivo targeting of cytosine-5 DNA methylation by zinc-finger proteins

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Prediction of methylated CpGs in DNA sequences using a support vector machine

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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DNA methylation and human disease

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Predicting methylation status of CpG islands in the human brain

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Quantifying similarity between motifs

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https://pubmed.ncbi.nlm.nih.gov/30967120

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Predicting DNA methylation susceptibility using CpG flanking sequences

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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DNA methylation landscapes: provocative insights from epigenomics

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Histone methylation marks play important roles in predicting the methylation status of CpG islands

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Linking DNA methylation and histone modification: patterns and paradigms

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Profile analysis and prediction of tissue-specific CpG island methylation classes

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Principles and challenges of genomewide DNA methylation analysis

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https://pubmed.ncbi.nlm.nih.gov/30967120

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Functions of DNA methylation: islands, start sites, gene bodies and beyond

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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CpGIMethPred: computational model for predicting methylation status of CpG islands in human genome

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Predicting DNA methylation level across human tissues

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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1 reference

https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Computationally expanding infinium HumanMethylation450 BeadChip array data to reveal distinct DNA methylation patterns of rheumatoid arthritis

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Predicting CpG methylation levels by integrating Infinium HumanMethylation450 BeadChip array data

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning

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https://pubmed.ncbi.nlm.nih.gov/30967120

12 December 2020

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Identifiers

10.1186/S12864-019-5488-5

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9 September 2019

https://scigraph.springernature.com/pub.10.1186/s12864-019-5488-5

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