AIMC Topic: Epigenomics
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Identifying Depression Through Machine Learning Analysis of Omics Data: Scoping Review.
JMIR nursing
Jul 19, 2024
BACKGROUND: Depression is one of the most common mental disorders that affects >300 million people worldwide. There is a shortage of providers trained in the provision of mental health care, and the nursing workforce is essential in filling this gap....
Multi-omics based artificial intelligence for cancer research.
Advances in cancer research
Jul 9, 2024
With significant advancements of next generation sequencing technologies, large amounts of multi-omics data, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have been accumulated, offering an unprecedented opportunity ...
DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic craniofacial development.
HGG advances
May 24, 2024
Orofacial clefts (OFCs) are among the most common human congenital birth defects. Previous multiethnic studies have identified dozens of associated loci for both cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP). Although seve...
Epigenetic target identification strategy based on multi-feature learning.
Journal of biomolecular structure & dynamics
Oct 12, 2023
The identification of potential epigenetic targets for a known bioactive compound is essential and promising as more and more epigenetic drugs are used in cancer clinical treatment and the availability of chemogenomic data related to epigenetics incr...
Precision epigenetics provides a scalable pathway for improving coronary heart disease care globally.
Epigenomics
Sep 13, 2023
Coronary heart disease (CHD) is the world's leading cause of death. Up to 90% of all CHD deaths are preventable, but effective prevention of this mortality requires more scalable, precise methods for assessing CHD status and monitoring treatment resp...
Artificial intelligence and high-dimensional technologies in the theragnosis of systemic lupus erythematosus.
The Lancet. Rheumatology
Feb 20, 2023
Systemic lupus erythematosus is a complex, systemic autoimmune disease characterised by immune dysregulation. Pathogenesis is multifactorial, contributing to clinical heterogeneity and posing challenges for diagnosis and treatment. Although strides i...
Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer.
Future oncology (London, England)
Dec 2, 2021
This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Based on the survival-related representation features yielded by BiDNNs through integrating tr...
A deep learning approach to automate whole-genome prediction of diverse epigenomic modifications in plants.
The New phytologist
Aug 12, 2021
Epigenetic modifications function in gene transcription, RNA metabolism, and other biological processes. However, multiple factors currently limit the scientific utility of epigenomic datasets generated for plants. Here, using deep-learning approache...
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...
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