AIMC Topic: Epigenesis, Genetic
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ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2022
Epigenetic modifications have a vital role in gene expression and are linked to cellular processes such as differentiation, development, and tumorigenesis. Thus, the availability of reliable and accurate methods for identifying and defining these cha...
A hybrid metaheuristic-deep learning technique for the pan-classification of cancer based on DNA methylation.
BMC bioinformatics
Jul 11, 2022
BACKGROUND: DNA Methylation is one of the most important epigenetic processes that are crucial to regulating the functioning of the human genome without altering the DNA sequence. DNA Methylation data for cancer patients are becoming more accessible ...
Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations, and Experiences.
Molecular nutrition & food research
Jul 10, 2022
With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) becomes a new scientific field and the first commercial offerings of genotype-ba...
Integrating Long-Range Regulatory Interactions to Predict Gene Expression Using Graph Convolutional Networks.
Journal of computational biology : a journal of computational molecular cell biology
Mar 21, 2022
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Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes.
Methods (San Diego, Calif.)
Dec 13, 2021
As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine (6 mA), plays an essential role in various cellular processes and disease pathogenesis. Therefore, accurately identifying 6 mA modifications is necessary for a ...
Profiling epigenetic age in single cells.
Nature aging
Dec 9, 2021
DNA methylation dynamics emerged as a promising biomarker of mammalian aging, with multivariate machine learning models ('epigenetic clocks') enabling measurement of biological age in bulk tissue samples. However, intrinsically sparse and binarized m...
Systems biology and machine learning approaches identify drug targets in diabetic nephropathy.
Scientific reports
Dec 6, 2021
Diabetic nephropathy (DN), the leading cause of end-stage renal disease, has become a massive global health burden. Despite considerable efforts, the underlying mechanisms have not yet been comprehensively understood. In this study, a systematic appr...
Regression Analysis
Principal Component Analysis
Linear Models
Support Vector Machine
Cluster Analysis
MicroRNAs
Mice, Inbred DBA
Kidney Cortex
Kidney Medulla
Chemistry, Pharmaceutical
Microarray Analysis
Oligonucleotide Array Sequence Analysis
Mice
Diabetic Nephropathies
Computational Biology
Systems Biology
Epigenesis, Genetic
Signal Transduction
Drug Design
Gene Expression Profiling
Gene Regulatory Networks
Animals
Male
Global Health
Machine Learning
Humans
Algorithms
Predicting environmentally responsive transgenerational differential DNA methylated regions (epimutations) in the genome using a hybrid deep-machine learning approach.
BMC bioinformatics
Nov 30, 2021
BACKGROUND: Deep learning is an active bioinformatics artificial intelligence field that is useful in solving many biological problems, including predicting altered epigenetics such as DNA methylation regions. Deep learning (DL) can learn an informat...
An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila.
Genome biology
Nov 8, 2021
BACKGROUND: Enhancers are non-coding regions of the genome that control the activity of target genes. Recent efforts to identify active enhancers experimentally and in silico have proven effective. While these tools can predict the locations of enhan...
Effective gene expression prediction from sequence by integrating long-range interactions.
Nature methods
Oct 4, 2021
How noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction a...
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