AIMC Topic: Histones
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Evaluating the informativeness of deep learning annotations for human complex diseases.
Nature communications
Sep 17, 2020
Deep learning models have shown great promise in predicting regulatory effects from DNA sequence, but their informativeness for human complex diseases is not fully understood. Here, we evaluate genome-wide SNP annotations from two previous deep learn...
In vitro and in silico genetic toxicity screening of flavor compounds and other ingredients in tobacco products with emphasis on ENDS.
Journal of applied toxicology : JAT
Jul 13, 2020
Electronic nicotine delivery systems (ENDS) are regulated tobacco products and often contain flavor compounds. Given the concern of increased use and the appeal of ENDS by young people, evaluating the potential of flavors to induce DNA damage is impo...
Humans
Machine Learning
Biomarkers
Animals
Consumer Product Safety
Flow Cytometry
Histones
Tumor Suppressor Protein p53
Risk Assessment
Cell Line
Electronic Nicotine Delivery Systems
Flavoring Agents
Mice
Quantitative Structure-Activity Relationship
Models, Molecular
Phosphorylation
Rats
Mutagenicity Tests
DNA Damage
CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection.
Scientific reports
May 13, 2020
ChIP-seq is one of the core experimental resources available to understand genome-wide epigenetic interactions and identify the functional elements associated with diseases. The analysis of ChIP-seq data is important but poses a difficult computation...
A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information.
BMC genomics
Dec 27, 2019
BACKGROUND: The three-dimensional (3D) structure of chromatins plays significant roles during cell differentiation and development. Hi-C and other 3C-based technologies allow us to look deep into the chromatin architectures. Many studies have suggest...
Identification of potential histone deacetylase1 (HDAC1) inhibitors using multistep virtual screening approach including SVM model, pharmacophore modeling, molecular docking and biological evaluation.
Journal of biomolecular structure & dynamics
Sep 9, 2019
Histone Deacetylases (HDACs) play a significant role in the regulation of gene expression by modifying histones and non-histone substrates. Since they are key regulators in the reversible epigenetic mechanism, they are considered as promising drug ta...
Visualizing complex feature interactions and feature sharing in genomic deep neural networks.
BMC bioinformatics
Jul 19, 2019
BACKGROUND: Visualization tools for deep learning models typically focus on discovering key input features without considering how such low level features are combined in intermediate layers to make decisions. Moreover, many of these methods examine ...
DeepHistone: a deep learning approach to predicting histone modifications.
BMC genomics
Apr 4, 2019
MOTIVATION: Quantitative detection of histone modifications has emerged in the recent years as a major means for understanding such biological processes as chromosome packaging, transcriptional activation, and DNA damage. However, high-throughput exp...
Enhancer prediction with histone modification marks using a hybrid neural network model.
Methods (San Diego, Calif.)
Mar 21, 2019
Enhancer is a DNA sequence of a genome that controls transcription of downstream target genes. Enhancers are known to be associated with certain epigenetic signatures. Machine learning tools, such as CSI-ANN, ChromHMM, and RFECS, were developed for p...
A machine learning-based prediction model of H3K27M mutations in brainstem gliomas using conventional MRI and clinical features.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Aug 7, 2018
BACKGROUND: H3K27M is the most frequent mutation in brainstem gliomas (BSGs), and it has great significance in the differential diagnosis, prognostic prediction and treatment strategy selection of BSGs. There has been a lack of reliable noninvasive m...
A Cascaded Deep Convolutional Neural Network for Joint Segmentation and Genotype Prediction of Brainstem Gliomas.
IEEE transactions on bio-medical engineering
Jun 8, 2018
GOAL: Automatic segmentation of brainstem gliomas and prediction of genotype (H3 K27M) mutation status based on magnetic resonance (MR) images are crucial but challenging tasks for computer-aided diagnosis in neurosurgery. In this paper, we present a...
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