AIMC Topic: Chromatin

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Identification of Gene Regulatory Networks from Single-Cell Expression Data.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Single-cell RNAseq is an emerging technology that allows the quantification of gene expression in individual cells. In plants, single-cell sequencing technology has been applied to generate root cell expression maps under many experimental conditions...
Single-Cell Analysis RNA-Seq Gene Regulatory Networks Machine Learning Software Programming Languages Chromatin Chromatin Immunoprecipitation Sequencing Computational Biology Sequence Analysis, DNA
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Graph convolutional networks for epigenetic state prediction using both sequence and 3D genome data.

Bioinformatics (Oxford, England) Dec 30, 2020
MOTIVATION: Predictive models of DNA chromatin profile (i.e. epigenetic state), such as transcription factor binding, are essential for understanding regulatory processes and developing gene therapies. It is known that the 3D genome, or spatial struc...
Neural Networks, Computer Genome Epigenesis, Genetic Epigenomics Chromatin
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Combining Deep Learning with Handcrafted Features for Cell Nuclei Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Segmentation of cell nuclei in fluorescence microscopy images provides valuable information about the shape and size of the nuclei, its chromatin texture and DNA content. It has many applications such as cell tracking, counting and classification. In...
Algorithms Cell Nucleus Chromatin Deep Learning Microscopy, Fluorescence
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HiCNN: a very deep convolutional neural network to better enhance the resolution of Hi-C data.

Bioinformatics (Oxford, England) Nov 1, 2019
MOTIVATION: High-resolution Hi-C data are indispensable for the studies of three-dimensional (3D) genome organization at kilobase level. However, generating high-resolution Hi-C data (e.g. 5 kb) by conducting Hi-C experiments needs millions of mammal...
Neural Networks, Computer Software Animals Humans Chromosomes Chromatin Mice Genome
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GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs.

Bioinformatics (Oxford, England) Jul 15, 2019
SUMMARY: Support Vector Machines with gapped k-mer kernels (gkm-SVMs) have been used to learn predictive models of regulatory DNA sequence. However, interpreting predictive sequence patterns learned by gkm-SVMs can be challenging. Existing interpreta...
Chromatin Protein Binding Support Vector Machine
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DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learning.

Nucleic acids research Jun 4, 2019
Interactions between regulatory elements are of crucial importance for the understanding of transcriptional regulation and the interpretation of disease mechanisms. Hi-C technique has been developed for genome-wide detection of chromatin contacts. Ho...
Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid Chromatin High-Throughput Nucleotide Sequencing Gene Expression Regulation Genome-Wide Association Study Computational Biology Humans Cells, Cultured Deep Learning Algorithms
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Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.

Bioinformatics (Oxford, England) Sep 1, 2018
MOTIVATION: Transcription factors bind regulatory DNA sequences in a combinatorial manner to modulate gene expression. Deep neural networks (DNNs) can learn the cis-regulatory grammars encoded in regulatory DNA sequences associated with transcription...
Protein Binding Genomics Neural Networks, Computer Chromatin DNA High-Throughput Nucleotide Sequencing Binding Sites Transcription Factors Sequence Analysis, DNA
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Chromatin accessibility prediction via a hybrid deep convolutional neural network.

Bioinformatics (Oxford, England) Mar 1, 2018
MOTIVATION: A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and p...
Humans Neural Networks, Computer Software Regulatory Sequences, Nucleic Acid Genomics Chromatin Sequence Analysis, DNA Genome, Human
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Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

Bioinformatics (Oxford, England) Jul 15, 2017
MOTIVATION: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing...
Humans Neural Networks, Computer Software Chromatin Computational Biology Cell Line
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HIPred: an integrative approach to predicting haploinsufficient genes.

Bioinformatics (Oxford, England) Jun 15, 2017
MOTIVATION: A major cause of autosomal dominant disease is haploinsufficiency, whereby a single copy of a gene is not sufficient to maintain the normal function of the gene. A large proportion of existing methods for predicting haploinsufficiency inc...
Chromatin Haploinsufficiency Sequence Analysis, RNA Protein Interaction Maps Genome, Human Epigenesis, Genetic Genomics Histones Sequence Analysis, DNA Humans Machine Learning
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