AIMC Topic: Histones

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DeepHistone: a deep learning approach to predicting histone modifications.

BMC genomics
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.)
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
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
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...

Label-free detection of histone based on cationic conjugated polymer-mediated fluorescence resonance energy transfer.

Talanta
A simple and homogeneous histone assay is developed based on histone-induced DNA compressing coupled with cationic conjugated polymer (CCP)-mediated fluorescence resonance energy transfer (FRET). In this strategy, the CCP serves as the FRET donor and...

Identify and analysis crotonylation sites in histone by using support vector machines.

Artificial intelligence in medicine
OBJECTIVE: Lysine crotonylation (Kcr) is a newly discovered histone posttranslational modification, which is specifically enriched at active gene promoters and potential enhancers in mammalian cell genomes. Although lysine crotonylation sites can be ...

Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.

BMC systems biology
BACKGROUND: Gene expression is mediated by specialized cis-regulatory modules (CRMs), the most prominent of which are called enhancers. Early experiments indicated that enhancers located far from the gene promoters are often responsible for mediating...

eRFSVM: a hybrid classifier to predict enhancers-integrating random forests with support vector machines.

Hereditas
BACKGROUND: Enhancers are tissue specific distal regulation elements, playing vital roles in gene regulation and expression. The prediction and identification of enhancers are important but challenging issues for bioinformatics studies. Existing comp...

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

Nucleic acids research
Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the te...