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DNA Methylation

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Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral Palsy.

International journal of molecular sciences
The etiology of cerebral palsy (CP) is complex and remains inadequately understood. Early detection of CP is an important clinical objective as this improves long term outcomes. We performed genome-wide DNA methylation analysis to identify epigenomic...

Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.

IEEE/ACM transactions on computational biology and bioinformatics
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...

MRCNN: a deep learning model for regression of genome-wide DNA methylation.

BMC genomics
BACKGROUND: Determination of genome-wide DNA methylation is significant for both basic research and drug development. As a key epigenetic modification, this biochemical process can modulate gene expression to influence the cell differentiation which ...

Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model.

IEEE/ACM transactions on computational biology and bioinformatics
DNA methylation plays an important role in the regulation of some biological processes. Up to now, with the development of machine learning models, there are several sequence-based deep learning models designed to predict DNA methylation states, whic...

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Journal of psychiatric research
Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigeneti...

Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features.

Genes
Accurate prognosis of patients with cancer is important for the stratification of patients, the optimization of treatment strategies, and the design of clinical trials. Both clinical features and molecular data can be used for this purpose, for insta...

Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

Genes
It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrinsic differences are closely related to clinical diagnosis and designation of treatment plans. With the accumulation of biological and medicine datasets...

Predicting overall survival of patients with hepatocellular carcinoma using a three-category method based on DNA methylation and machine learning.

Journal of cellular and molecular medicine
Hepatocellular carcinoma (HCC) is closely associated with abnormal DNA methylation. In this study, we analyzed 450K methylation chip data from 377 HCC samples and 50 adjacent normal samples in the TCGA database. We screened 47,099 differentially meth...

Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier.

Breast cancer research : BCR
BACKGROUND: BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other ...

Manganese oxide nanoparticles induce genotoxicity and DNA hypomethylation in the moss Physcomitrella patens.

Mutation research. Genetic toxicology and environmental mutagenesis
The genotoxicity of nanoparticles is a major concern for nano-safety appraisal in the bryophytes as they are the primary colonizers of bare land, indicators of atmospheric pollution and excellent accumulators of trace metals. The present study for th...