Search results for " Recurrent neural networks"

showing 4 items of 4 documents

Deep learning architectures for prediction of nucleosome positioning from sequences data

2018

Abstract Background Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several biological studies have shown that the nucleosome positioning influences the regulation of cell type-specific gene activities. Moreover, computational studies have shown evidence of sequence specificity concerning the DNA fragment wrapped into nucleosomes, clearly underlined by the organization of particular DNA substrings. As the main consequence, the identification of nucleosomes on a genomic scale has been successfully performed by com…

0301 basic medicineComputer scienceCellBiochemistrychemistry.chemical_compound0302 clinical medicineStructural Biologylcsh:QH301-705.5Nucleosome classificationSequenceSettore INF/01 - InformaticabiologyApplied MathematicsEpigeneticComputer Science ApplicationsChromatinNucleosomesmedicine.anatomical_structurelcsh:R858-859.7EukaryoteDNA microarrayDatabases Nucleic AcidComputational biologySaccharomyces cerevisiaelcsh:Computer applications to medicine. Medical informatics03 medical and health sciencesDeep LearningmedicineNucleosomeAnimalsHumansEpigeneticsMolecular BiologyGeneBase Sequencebusiness.industryDeep learningResearchReproducibility of Resultsbiology.organism_classificationYeastNucleosome classification Epigenetic Deep learning networks Recurrent neural networks030104 developmental biologylcsh:Biology (General)chemistryRecurrent neural networksROC CurveDeep learning networksArtificial intelligenceNeural Networks Computerbusiness030217 neurology & neurosurgeryDNABMC Bioinformatics
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Deep learning network for exploiting positional information in nucleosome related sequences

2017

A nucleosome is a DNA-histone complex, wrapping about 150 pairs of double-stranded DNA. The role of nucleosomes is to pack the DNA into the nucleus of the Eukaryote cells to form the Chromatin. Nucleosome positioning genome wide play an important role in the regulation of cell type-specific gene activities. Several biological studies have shown sequence specificity of nucleosome presence, clearly underlined by the organization of precise nucleotides substrings. Taking into consideration such advances, the identification of nucleosomes on a genomic scale has been successfully performed by DNA sequence features representation and classical supervised classification methods such as Support Vec…

0301 basic medicineComputer scienceSpeech recognitionCell02 engineering and technologyComputational biologyGenomeDNA sequencing03 medical and health scienceschemistry.chemical_compoundDeep Learning0202 electrical engineering electronic engineering information engineeringmedicineNucleosomeNucleotideGeneSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionichemistry.chemical_classificationSequenceSettore INF/01 - Informaticabiologybusiness.industryDeep learningnucleosomebiology.organism_classificationSubstringChromatinIdentification (information)030104 developmental biologymedicine.anatomical_structurechemistry020201 artificial intelligence & image processingEukaryoteNucleosome classification Epigenetic Deep learning networks Recurrent Neural NetworksArtificial intelligencebusinessDNA
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Recurrent Deep Neural Networks for Nucleosome Classification

2020

Nucleosomes are the fundamental repeating unit of chromatin. A nucleosome is an 8 histone proteins complex, in which approximately 147–150 pairs of DNA bases bind. Several biological studies have clearly stated that the regulation of cell type-specific gene activities are influenced by nucleosome positioning. Bioinformatic studies have improved those results showing proof of sequence specificity in nucleosomes’ DNA fragment. In this work, we present a recurrent neural network that uses nucleosome sequence features representation for their classification. In particular, we implement an architecture which stacks convolutional and long short-term memory layers, with the main purpose to avoid t…

0301 basic medicineSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionibiologySettore INF/01 - InformaticaComputer scienceComputational biologyChromatin03 medical and health scienceschemistry.chemical_compound030104 developmental biologyHistoneRecurrent neural networkchemistryFragment (logic)biology.proteinNucleosomeNucleosome classification Epigenetic Deep learning networks Recurrent Neural NetworksGeneDNASequence (medicine)
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Deep Learning Architectures for DNA Sequence Classification

2016

DNA sequence classification is a key task in a generic computational framework for biomedical data analysis, and in recent years several machine learning technique have been adopted to successful accomplish with this task. Anyway, the main difficulty behind the problem remains the feature selection process. Sequences do not have explicit features, and the commonly used representations introduce the main drawback of the high dimensionality. For sure, machine learning method devoted to supervised classification tasks are strongly dependent on the feature extraction step, and in order to build a good representation it is necessary to recognize and measure meaningful details of the items to cla…

DNA sequence classificatio Convolutional Neural Networks Recurrent Neural Networks Deep learning networksSettore INF/01 - Informatica
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