Search results for "Micro"

showing 10 items of 23412 documents

A Methodology to Study Pseudogenized lincRNAs

2021

Long intergenic noncoding RNAs (lincRNAs) are known to be tissue specifically expressed and able to regulate functional protein-coding genes: some can even act as competing endogenous RNAs (ceRNAs), because microRNAs can bind to them instead of the corresponding mRNA binding sites. Some lincRNAs contain remnants of protein-coding sequences and it has been hypothesized that they might arise after a pseudogenization processes. However, a major limitation in the study of such phenomenon is the lack of proper computational tools designed to align/analyze protein-coding sequences and noncoding sequences. To overcome this limitation, we published a method that finds the remnants of protein-coding…

0301 basic medicineCompeting endogenous RNAPseudogeneSequence alignmentComputational biologyBiology03 medical and health sciences030104 developmental biology0302 clinical medicineIntergenic regionmicroRNASingle pointGene030217 neurology & neurosurgerySequence (medicine)
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Large-scale identification of functional microRNA targeting reveals cooperative regulation of the hemostatic system.

2018

Essentials MicroRNAs (miRNAs) regulate the molecular networks controlling biological functions such as hemostasis. We utilized novel methods to analyze miRNA-mediated regulation of the hemostatic system. 52 specific miRNA interactions with 11 key hemostatic associated genes were identified. Functionality and drugability of miRNA-19b-3p against antithrombin were demonstrated in vivo. SUMMARY: Background microRNAs (miRNAs) confer robustness to complex molecular networks regulating biological functions. However, despite the involvement of miRNAs in almost all biological processes, and the importance of the hemostatic system for a multitude of actions in and beyond blood coagulation, the role o…

0301 basic medicineComputational biologyBiologyAntithrombinsHemostatics03 medical and health sciencesMiceCell Line TumormicroRNAGene silencingAnimalsHumansGene SilencingBiomarker discoveryGene3' Untranslated RegionsHemostasisThree prime untranslated regionRNARobustness (evolution)Computational BiologyHigh-Throughput Nucleotide SequencingThrombosisHematologyMice Inbred C57BLMicroRNAs030104 developmental biologyHemostasisBiomarkersPlasmidsJournal of thrombosis and haemostasis : JTH
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HPG pore: an efficient and scalable framework for nanopore sequencing data.

2016

The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. Here we present HPG Pore, a toolkit for …

0301 basic medicineComputer scienceApplied MathematicsDistributed computingDNASequence Analysis DNAData scienceBiochemistryComputer Science Applications03 medical and health scienceschemistry.chemical_compoundNanoporeNanopores030104 developmental biology0302 clinical medicinechemistryStructural Biology030220 oncology & carcinogenesisScalabilityNanopore sequencingDNA microarrayThroughput (business)Molecular BiologyDNASoftwareBMC bioinformatics
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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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EFMviz

2020

Elementary Flux Modes (EFMs) are a tool for constraint-based modeling and metabolic network analysis. However, systematic and automated visualization of EFMs, capable of integrating various data types is still a challenge. In this study, we developed an extension for the widely adopted COBRA Toolbox, EFMviz, for analysis and graphical visualization of EFMs as networks of reactions, metabolites and genes. The analysis workflow offers a platform for EFM visualization to improve EFM interpretability by connecting COBRA toolbox with the network analysis and visualization software Cytoscape. The biological applicability of EFMviz is demonstrated in two use cases on medium (Escherichia coli, iAF1…

0301 basic medicineComputer scienceEndocrinology Diabetes and Metabolismgenome-scale metabolic modelslcsh:QR1-502computer.software_genreBiochemistryData typelcsh:MicrobiologySBML03 medical and health sciences0302 clinical medicineData visualizationGraph drawingProtocolACETATEdata visualizationCELLSBMLCYTOSCAPEMolecular BiologyGENE-EXPRESSIONSoftware visualizationbusiness.industryPATHWAY ANALYSISnetwork visualizationelementary flux modesToolboxVisualization030104 developmental biologyWorkflowDEFINITIONESCHERICHIA-COLIGROWTHData miningbusinesscomputerSET030217 neurology & neurosurgeryMetabolites
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Twitter as a tool for teaching and communicating microbiology: the #micromoocsem initiative

2016

López-Goñi, Ignacio et al.

0301 basic medicineComputer scienceHuman immunodeficiency virus (HIV)medicine.disease_causeMicrobiologíaSocial networksMultidisciplinary approachScience communicationDuration (project management)Biology (General)lcsh:QH301-705.5X300Centro Oceanográfico de Gijónmedia_commoneducation.field_of_studylcsh:LC8-66914. Education05 social sciences050301 educationC500Special aspects of educationsocial networkGeneral Agricultural and Biological SciencesP990AcuiculturaQH301-705.5media_common.quotation_subject030106 microbiologyPopulationTwitterAcademic practiceTips & Toolscollaborative teachingMOOCMicrobiologyGeneral Biochemistry Genetics and Molecular BiologyEducationMicrobiology03 medical and health sciencesactive learningmedicineInstitutioneducationGeneral Immunology and MicrobiologyLC8-6691lcsh:Special aspects of educationTeachingmicrobiologySocial learningsocial learningMicroMOOCSEMlcsh:Biology (General)0503 education
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Quantitatively characterizing drug-induced arrhythmic contractile motions of human stem cell-derived cardiomyocytes.

2018

Quantification of abnormal contractile motions of cardiac tissue has been a noteworthy challenge and significant limitation in assessing and classifying the drug-induced arrhythmias (i.e. Torsades de pointes). To overcome these challenges, researchers have taken advantage of computational image processing tools to measure contractile motion from cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs). However, the amplitude and frequency analysis of contractile motion waveforms doesn't produce sufficient information to objectively classify the degree of variations between two or more sets of cardiac contractile motions. In this paper, we generated contractile motion dat…

0301 basic medicineComputer scienceImage ProcessingComputational algorithmArrhythmiasRegenerative MedicineCardiovascularApplied Microbiology and Biotechnologyphase space reconstruction0302 clinical medicineComputer-AssistedImage Processing Computer-AssistedMyocytes CardiacComputingMilieux_MISCELLANEOUS[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingStem Cell Research - Induced Pluripotent Stem Cell - HumanOptical ImagingHeart DiseaseNetworking and Information Technology R&DStem cellBiological systemCardiacBiotechnologyCytological TechniquesInduced Pluripotent Stem CellsOptical flowTorsades de pointesImage processingBioengineeringarrhythmiaArticlebiosignal processingoptical flow03 medical and health sciencesMotionMatch movingmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumansMyocytesStem Cell Research - Induced Pluripotent Stem CellCardiac arrhythmiaArrhythmias CardiacTissue physiologymedicine.diseaseStem Cell ResearchMyocardial Contractioncardiac motion030104 developmental biology030217 neurology & neurosurgerySoftware
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Transcriptome Analysis of PA Gain and Loss of Function Mutants

2017

Functional genomics has become a forefront methodology for plant science thanks to the widespread development of microarray technology. While technical difficulties associated with the process of obtaining raw expression data have been diminishing, allowing the appearance of tremendous amounts of transcriptome data in different databases, a common problem using "omic" technologies remains: the interpretation of these data and the inference of its biological meaning. In order to assist to this complex task, a wide variety of software tools have been developed. In this chapter we describe our current workflow of the application of some of these analyses. We have used it to compare the transcr…

0301 basic medicineComputer scienceMicroarray analysis techniquesProcess (engineering)MutantComputational biologyOmicsTranscriptomeGene expression profiling03 medical and health sciences030104 developmental biologyMolecular Sequence AnnotationGene chip analysisFunctional genomicsLoss function
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Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy

2017

Neuronal networks are often characterized by their spiking and bursting statistics. Previously, we introducedan adaptive burst analysis methodwhich enhances the analysis power for neuronal networks with highly varying firing dynamics. The adaptation is based on single channels analyzing each element of a network separately. Such kind of analysis was adequate for the assessment of local behavior, where the analysis focuses on the neuronal activity in the vicinity of a single electrode. However, the assessment of the whole network may be hampered, if parts of the network are analyzed using different rules. Here, we test how using multiple channels and measurement time points affect adaptive b…

0301 basic medicineComputer scienceNeuroscience (miscellaneous)Interval (mathematics)Machine learningcomputer.software_genreta3112lcsh:RC321-57103 medical and health sciencesCellular and Molecular NeuroscienceBursting0302 clinical medicineMoving averageHistogramMethodsCluster analysislcsh:Neurosciences. Biological psychiatry. Neuropsychiatryta113network classificationbusiness.industryEmphasis (telecommunications)Pattern recognition217 Medical engineeringlaskennallinen neurotiede113 Computer and information sciencesPower (physics)030104 developmental biologymicroelectrode arraysburst detectionburst synchronySpike (software development)Artificial intelligenceneuronal networksbusinesscomputer030217 neurology & neurosurgeryNeurosciencecomputational neuroscienceFrontiers in Computational Neuroscience
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Spectral entropy based neuronal network synchronization analysis based on microelectrode array measurements

2016

Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from differ…

0301 basic medicineComputer scienceNeuroscience (miscellaneous)ta3112Radio spectrumSynchronizationlcsh:RC321-571Correlation03 medical and health sciencesCellular and Molecular Neuroscience0302 clinical medicineBiological neural networkMethodsTime domainlcsh:Neurosciences. Biological psychiatry. NeuropsychiatrySimulationEvent (probability theory)rat cortical cellsMEAmicroelectrode array213 Electronic automation and communications engineering electronicsspectral entropyInformation processingCorrectiondeveloping neuronal networksMultielectrode array217 Medical engineering030104 developmental biologycorrelationmouse cortical cellsBiological systemsynchronization030217 neurology & neurosurgeryNeuroscienceFrontiers in Computational Neuroscience
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