AIMC Topic: Chromatin

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A supervised learning framework for chromatin loop detection in genome-wide contact maps.

Nature communications Jul 9, 2020
Accurately predicting chromatin loops from genome-wide interaction matrices such as Hi-C data is critical to deepening our understanding of proper gene regulation. Current approaches are mainly focused on searching for statistically enriched dots on ...
Humans Organ Specificity K562 Cells Genome Chromatin Databases, Genetic Sequence Analysis, DNA Supervised Machine Learning Species Specificity
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Discriminant analysis and interpretation of nuclear chromatin distribution and coarseness using gray-level co-occurrence matrix features for lobular endocervical glandular hyperplasia.

Diagnostic cytopathology May 6, 2020
BACKGROUND: Lobular endocervical glandular hyperplasia (LEGH) is a disease considered to be the origin of tumorigenesis of minimal deviation adenocarcinoma, which has characteristic expression in the gastric pyloric mucosa. It is difficult to diagnos...
Image Interpretation, Computer-Assisted Hyperplasia Chromatin Adenocarcinoma Support Vector Machine Humans Discriminant Analysis Female Aged Adult Uterine Cervical Neoplasms Middle Aged Papanicolaou Test
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DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.

Genes & genetic systems Mar 26, 2020
Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with ...
Genome, Plant Arabidopsis Chromatin High-Throughput Nucleotide Sequencing Data Analysis Machine Learning Molecular Sequence Annotation Computational Biology Crowdsourcing Japan Databases, Nucleic Acid
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DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure.

Genome biology Mar 26, 2020
Non-coding variants have been shown to be related to disease by alteration of 3D genome structures. We propose a deep learning method, DeepMILO, to predict the effects of variants on CTCF/cohesin-mediated insulator loops. Application of DeepMILO on v...
Chromatin CCCTC-Binding Factor Chromosomal Proteins, Non-Histone Insulator Elements Mutation Whole Genome Sequencing Cell Cycle Proteins Cohesins Humans Neoplasms Deep Learning Cell Line, Tumor
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Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data.

Nature communications Mar 3, 2020
Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biolog...
Algorithms Reproducibility of Results Genomics Cluster Analysis Humans Neural Networks, Computer Data Analysis Epigenome K562 Cells Computer Graphics Unsupervised Machine Learning Chromatin Gene Expression Markov Chains
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Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

eLife Jan 27, 2020
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict e...
Genetic Predisposition to Disease Polymorphism, Single Nucleotide Epigenomics Signal Transduction Models, Theoretical Chromatin Islets of Langerhans Humans Deep Learning Genome-Wide Association Study Diabetes Mellitus, Type 2
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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...
Neural Networks, Computer Algorithms ROC Curve Protein Binding Area Under Curve Histones Chromatin Histone Code
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Ranking of non-coding pathogenic variants and putative essential regions of the human genome.

Nature communications Nov 20, 2019
A gene is considered essential if loss of function results in loss of viability, fitness or in disease. This concept is well established for coding genes; however, non-coding regions are thought less likely to be determinants of critical functions. H...
Genes, Reporter Chromatin Nucleic Acid Conformation Introns INDEL Mutation Supervised Machine Learning Computer Simulation Enhancer Elements, Genetic Genetic Variation DNA Genome, Human Gene Expression Mutation Humans
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Deep learning-based selection of human sperm with high DNA integrity.

Communications biology Jul 3, 2019
Despite the importance of sperm DNA to human reproduction, currently no method exists to assess individual sperm DNA quality prior to clinical selection. Traditionally, skilled clinicians select sperm based on a variety of morphological and motility ...
DNA Fragmentation Deep Learning Normal Distribution Humans Spermatozoa DNA Neural Networks, Computer Learning Curve Bayes Theorem Healthy Volunteers Male Chromatin Semen Analysis
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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...
Protein Processing, Post-Translational Gene Expression Regulation Histones Chromosome Mapping Chromatin Humans Deep Learning Chromatin Immunoprecipitation Polymorphism, Single Nucleotide Epigenomics
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