AIMC Topic: Sequence Analysis, DNA

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Prediction of DNase I hypersensitive sites in plant genome using multiple modes of pseudo components.

Analytical biochemistry Mar 28, 2018
DNase I hypersensitive sites (DHSs) are accessible chromatin zones hypersensitive to DNase I endonucleases in plant genome. DHSs have been used as markers for the presence of transcriptional regulatory elements. It is an important complement to devel...
Sequence Analysis, DNA Genome, Plant Arabidopsis Deoxyribonuclease I Machine Learning Algorithms Response Elements
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Generalising better: Applying deep learning to integrate deleteriousness prediction scores for whole-exome SNV studies.

PloS one Mar 14, 2018
Many automatic classifiers were introduced to aid inference of phenotypical effects of uncategorised nsSNVs (nonsynonymous Single Nucleotide Variations) in theoretical and medical applications. Lately, several meta-estimators have been proposed that ...
Exome Models, Genetic Machine Learning Sequence Analysis, DNA Polymorphism, Single Nucleotide Internet
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iRSpot-PDI: Identification of recombination spots by incorporating dinucleotide property diversity information into Chou's pseudo components.

Genomics Mar 13, 2018
Recombination spot identification plays an important role in revealing genome evolution and developing DNA function study. Although some computational methods have been proposed, extracting discriminatory information embedded in DNA properties has no...
Computational Biology Support Vector Machine Sequence Analysis, DNA Software Recombination, Genetic Genomics
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Molecular identification and in vitro antifungal susceptibility of Scedosporium complex isolates from high-human-activity sites in Mexico.

Mycologia Mar 1, 2018
The genus Scedosporium is a complex of ubiquitous moulds associated with a wide spectrum of clinical entities, with high mortality principally in immunocompromised hosts. Ecology of these microorganisms has been studied performing isolations from env...
Soil Microbiology Antifungal Agents Phylogeny DNA, Ribosomal Spacer Sequence Analysis, DNA Microbial Sensitivity Tests Scedosporium Tubulin Cluster Analysis Mexico DNA, Fungal
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Graphical classification of DNA sequences of HLA alleles by deep learning.

Human cell Jan 11, 2018
Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence "Deep Learning (Stacked autoencoder)". Nucleotide sequence data corresponding to the length of 822 bp, collected from the Immuno...
HLA-A Antigens Humans Artificial Intelligence Base Sequence Sequence Analysis, DNA Databases, Nucleic Acid Alleles
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The potential of circulating tumor DNA methylation analysis for the early detection and management of ovarian cancer.

Genome medicine Dec 22, 2017
BACKGROUND: Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancer...
Aged Adult Humans Female DNA Methylation Ovarian Neoplasms Cell-Free Nucleic Acids Biomarkers, Tumor Random Allocation Middle Aged Sequence Analysis, DNA
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Targeted bisulfite sequencing identified a panel of DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC).

Clinical epigenetics Dec 15, 2017
BACKGROUND: DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC).
Pseudogenes Repressor Proteins Serine-Threonine Kinase 3 CpG Islands Promoter Regions, Genetic Sensitivity and Specificity Esophageal Squamous Cell Carcinoma Biomarkers, Tumor Protein Serine-Threonine Kinases Male DNA-Binding Proteins Humans Middle Aged Databases, Genetic Female Esophageal Neoplasms Machine Learning Logistic Models Sequence Analysis, DNA Carcinoma, Squamous Cell Epigenesis, Genetic DNA Methylation Aged Early Detection of Cancer
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Decontaminating eukaryotic genome assemblies with machine learning.

BMC bioinformatics Dec 1, 2017
BACKGROUND: High-throughput sequencing has made it theoretically possible to obtain high-quality de novo assembled genome sequences but in practice DNA extracts are often contaminated with sequences from other organisms. Currently, there are few exis...
Machine Learning High-Throughput Nucleotide Sequencing Genome Base Composition Caenorhabditis Animals Databases, Genetic Sequence Analysis, DNA DNA, Helminth
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[The potential of artificial intelligence in myology: a viewpoint from a non-robot].

Medecine sciences : M/S Nov 15, 2017
Humans Artificial Intelligence History, 20th Century Databases, Factual Muscles Genetic Testing Muscular Diseases High-Throughput Nucleotide Sequencing History, 21st Century Precision Medicine Inventions Sequence Analysis, DNA Medical Record Linkage
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ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.

BMC bioinformatics Nov 14, 2017
BACKGROUND: With the development of chromosomal conformation capturing techniques, particularly, the Hi-C technique, the study of the spatial conformation of a genome is becoming an important topic in bioinformatics and computational biology. The Hi-...
Chromatin Immunoprecipitation Histone Code CCCTC-Binding Factor Binding Sites Enhancer Elements, Genetic Chromosomes Animals Mice Genomics Unsupervised Machine Learning Promoter Regions, Genetic Sequence Analysis, DNA Cluster Analysis
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