AIMC Topic: Chromosomes

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ChrNet: A re-trainable chromosome-based 1D convolutional neural network for predicting immune cell types.

Genomics Apr 28, 2021
Cells from our immune system detect and kill pathogens to protect our body against various diseases. However, current methods for determining cell types have some major limitations, such as being time-consuming and with low throughput, etc. Immune ce...
Prognosis Single-Cell Analysis Cluster Analysis Humans Neural Networks, Computer Chromosomes
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CBCR: A Curriculum Based Strategy For Chromosome Reconstruction.

International journal of molecular sciences Apr 16, 2021
In this paper, we introduce a novel algorithm that aims to estimate chromosomes' structure from their Hi-C contact data, called Curriculum Based Chromosome Reconstruction (CBCR). Specifically, our method performs this three dimensional reconstruction...
Models, Genetic Chromosomes Chromosome Mapping Humans Machine Learning
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DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks.

IEEE transactions on medical imaging Nov 30, 2020
Chromosome enumeration is an essential but tedious procedure in karyotyping analysis. To automate the enumeration process, we develop a chromosome enumeration framework, DeepACEv2, based on the region based object detection scheme. The framework is d...
Neural Networks, Computer Chromosomes Karyotyping Metaphase
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Improving genomic prediction accuracy for meat tenderness in Nellore cattle using artificial neural networks.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie Feb 5, 2020
The goal of this study was to compare the predictive performance of artificial neural networks (ANNs) with Bayesian ridge regression, Bayesian Lasso, Bayes A, Bayes B and Bayes Cπ in estimating genomic breeding values for meat tenderness in Nellore c...
Neural Networks, Computer Polymorphism, Single Nucleotide Genotype Bayes Theorem Animals Cattle Genomics Linkage Disequilibrium Chromosomes Quantitative Trait, Heritable Meat Breeding Gene Frequency Pedigree Genome
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The Helitron family classification using SVM based on Fourier transform features applied on an unbalanced dataset.

Medical & biological engineering & computing Aug 17, 2019
Helitrons are mobile sequences which belong to the class 2 of eukaryotic transposons. Their specificity resides in their mechanism of transposition: the rolling circle mechanism. They play an important role in remodeling proteomes due to their abilit...
Chromosomes Genome, Helminth Databases as Topic Caenorhabditis elegans Fourier Analysis Animals Support Vector Machine
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Varifocal-Net: A Chromosome Classification Approach Using Deep Convolutional Networks.

IEEE transactions on medical imaging Mar 19, 2019
Chromosome classification is critical for karyotyping in abnormality diagnosis. To expedite the diagnosis, we present a novel method named Varifocal-Net for simultaneous classification of chromosome's type and polarity using deep convolutional networ...
Image Interpretation, Computer-Assisted Chromosomes Chromosome Disorders Karyotyping Female Male Supervised Machine Learning Neural Networks, Computer Algorithms Humans
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diploS/HIC: An Updated Approach to Classifying Selective Sweeps.

G3 (Bethesda, Md.) May 31, 2018
Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective s...
Neural Networks, Computer Selection, Genetic Chromosomes Image Processing, Computer-Assisted Machine Learning Recombination, Genetic Genotype Genome, Insect Animals Anopheles Base Sequence ROC Curve
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Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research Mar 27, 2018
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...
Models, Genetic Neural Networks, Computer Gene Expression Regulation Machine Learning Promoter Regions, Genetic Animals Humans Polymorphism, Single Nucleotide Chromosomes Computational Biology Regulatory Sequences, Nucleic Acid Gene Expression Profiling Epigenomics Genomics
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Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus.

Nature communications Feb 21, 2018
Although Hi-C technology is one of the most popular tools for studying 3D genome organization, due to sequencing cost, the resolution of most Hi-C datasets are coarse and cannot be used to link distal regulatory elements to their target genes. Here w...
Humans Deep Learning High-Throughput Nucleotide Sequencing Chromosomes Chromatin Assembly and Disassembly
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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-...
Histone Code Unsupervised Machine Learning CCCTC-Binding Factor Genomics Promoter Regions, Genetic Sequence Analysis, DNA Animals Enhancer Elements, Genetic Binding Sites Cluster Analysis Mice Chromosomes Chromatin Immunoprecipitation
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