AIMC Topic: Enhancer Elements, Genetic
Clear Filters Showing 61 to 70 of 75 articles
Supervised learning of enhancer-promoter specificity based on genome-wide perturbation studies highlights areas for improvement in learning.
Bioinformatics (Oxford, England)
Jun 3, 2024
MOTIVATION: Understanding the rules that govern enhancer-driven transcription remains a central unsolved problem in genomics. Now with multiple massively parallel enhancer perturbation assays published, there are enough data that we can utilize to le...
Enhancer-MDLF: a novel deep learning framework for identifying cell-specific enhancers.
Briefings in bioinformatics
Jan 22, 2024
Enhancers, noncoding DNA fragments, play a pivotal role in gene regulation, facilitating gene transcription. Identifying enhancers is crucial for understanding genomic regulatory mechanisms, pinpointing key elements and investigating networks governi...
HEAP: a task adaptive-based explainable deep learning framework for enhancer activity prediction.
Briefings in bioinformatics
Sep 20, 2023
Enhancers are crucial cis-regulatory elements that control gene expression in a cell-type-specific manner. Despite extensive genetic and computational studies, accurately predicting enhancer activity in different cell types remains a challenge, and t...
DeepITEH: a deep learning framework for identifying tissue-specific eRNAs from the human genome.
Bioinformatics (Oxford, England)
Jun 1, 2023
MOTIVATION: Enhancers are vital cis-regulatory elements that regulate gene expression. Enhancer RNAs (eRNAs), a type of long noncoding RNAs, are transcribed from enhancer regions in the genome. The tissue-specific expression of eRNAs is crucial in th...
Analysis of super-enhancer using machine learning and its application to medical biology.
Briefings in bioinformatics
May 19, 2023
The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the o...
scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.
Nucleic acids research
Jan 7, 2022
Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populati...
Eukaryotic Cells
Chromatin
Consensus Sequence
Promoter Regions, Genetic
Organ Specificity
Drosophila melanogaster
Molecular Sequence Annotation
Cell Lineage
Enhancer Elements, Genetic
Internet
Genetic Heterogeneity
Gene Expression Regulation
Databases, Genetic
Unsupervised Machine Learning
Humans
Software
Animals
Single-Cell Analysis
Gene Regulatory Networks
Mice
Deciphering the regulatory syntax of genomic DNA with deep learning.
Journal of biosciences
Jan 1, 2022
An organism's genome contains many sequence regions that perform diverse functions. Examples of such regions include genes, promoters, enhancers, and binding sites for regulatory proteins and RNAs. One of biology's most important open problems is how...
Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.
Briefings in bioinformatics
Nov 5, 2021
Enhancers are deoxyribonucleic acid (DNA) fragments which when bound by transcription factors enhance the transcription of related genes. Due to its sporadic distribution and similar fractions, identification of enhancers from the human genome seems ...
Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks.
Nucleic acids research
Oct 11, 2021
Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and und...
iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network.
Briefings in bioinformatics
Sep 2, 2021
DNase I hypersensitive site (DHS) refers to the hypersensitive region of chromatin for the DNase I enzyme. It is an important part of the noncoding region and contains a variety of regulatory elements, such as promoter, enhancer, and transcription fa...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823