AIMC Topic: Epigenomics
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Machine Learning in Epigenomics: Insights into Cancer Biology and Medicine.
Biochimica et biophysica acta. Reviews on cancer
Jul 7, 2021
The recent deluge of genome-wide technologies for the mapping of the epigenome and resulting data in cancer samples has provided the opportunity for gaining insights into and understanding the roles of epigenetic processes in cancer. However, the com...
Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos.
PloS one
May 24, 2021
Pregnancy rates for in vitro produced (IVP) embryos are usually lower than for embryos produced in vivo after ovarian superovulation (MOET). This is potentially due to alterations in their trophectoderm (TE), the outermost layer in physical contact w...
A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome.
Scientific reports
May 14, 2021
DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification responsible for many biological functions. Automated and accurate computational methods can help to identify 6mA sites in long genomes saving significant time and money...
Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease.
PloS one
Mar 31, 2021
We evaluated the utility of leucocyte epigenomic-biomarkers for Alzheimer's Disease (AD) detection and elucidates its molecular pathogeneses. Genome-wide DNA methylation analysis was performed using the Infinium MethylationEPIC BeadChip array in 24 l...
Epigenetic Target Fishing with Accurate Machine Learning Models.
Journal of medicinal chemistry
Mar 26, 2021
Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represe...
Integrated multi-omics analysis of ovarian cancer using variational autoencoders.
Scientific reports
Mar 18, 2021
Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., DNA, RNA, and proteins). Integrated multi-omics analysis of data from these levels is necessary to understand the aberrant cellular functions accountab...
Deep learning-based enhancement of epigenomics data with AtacWorks.
Nature communications
Mar 8, 2021
ATAC-seq is a widely-applied assay used to measure genome-wide chromatin accessibility; however, its ability to detect active regulatory regions can depend on the depth of sequencing coverage and the signal-to-noise ratio. Here we introduce AtacWorks...
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.
International journal of molecular sciences
Dec 26, 2020
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for t...
A pitfall for machine learning methods aiming to predict across cell types.
Genome biology
Nov 19, 2020
Machine learning models that predict genomic activity are most useful when they make accurate predictions across cell types. Here, we show that when the training and test sets contain the same genomic loci, the resulting model may falsely appear to p...
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