Search results for "Structural Biology."

showing 10 items of 822 documents

JANE: efficient mapping of prokaryotic ESTs and variable length sequence reads on related template genomes

2009

Abstract Background ESTs or variable sequence reads can be available in prokaryotic studies well before a complete genome is known. Use cases include (i) transcriptome studies or (ii) single cell sequencing of bacteria. Without suitable software their further analysis and mapping would have to await finalization of the corresponding genome. Results The tool JANE rapidly maps ESTs or variable sequence reads in prokaryotic sequencing and transcriptome efforts to related template genomes. It provides an easy-to-use graphics interface for information retrieval and a toolkit for EST or nucleotide sequence function prediction. Furthermore, we developed for rapid mapping an enhanced sequence align…

Computational biologyBiologylcsh:Computer applications to medicine. Medical informaticsBiochemistryGenomeUser-Computer InterfaceStructural BiologyDatabases Geneticlcsh:QH301-705.5Molecular BiologySequence (medicine)Expressed Sequence TagsWhole genome sequencingGeneticsInternetExpressed sequence tagGenomeBase SequencePhylumApplied MathematicsNucleic acid sequenceComputational BiologySequence Analysis DNAComputer Science Applicationslcsh:Biology (General)Single cell sequencinglcsh:R858-859.7DNA microarraySoftwareBMC Bioinformatics
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Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

Computer scienceAlgorismesPrediction by partial matchingCompression dissimilaritycomputer.software_genreBiochemistryProtein Structure SecondaryPhylogenetic studiesStructural BiologySequence Analysis ProteinDatabases Proteinlcsh:QH301-705.5Biological dataNCDApplied MathematicsGenomicsClassificationCDComputer Science ApplicationsBenchmarking:Informàtica::Informàtica teòrica [Àrees temàtiques de la UPC]Universal compression dissimilarityArea Under CurveMetric (mathematics)lcsh:R858-859.7Data miningAlgorithmsData compressionResearch Article:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Normalization (statistics)lcsh:Computer applications to medicine. Medical informaticsBioinformatics Sequence Alignment AlgorithmsSet (abstract data type)Similarity (network science)Normalized compression sissimilarityData compression (Computer science)AnimalsHumansAmino Acid SequenceMolecular BiologyBiologyDades -- Compressió (Informàtica)USMUniversal similarity metricProteinsUCDProtein Structure TertiaryData setGenòmicaStatistical classificationlcsh:Biology (General)ROC CurvecomputerSequence AlignmentSoftwareBMC bioinformatics
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Dynamic-shared Pharmacophore Approach as Tool to Design New Allosteric PRC2 Inhibitors, Targeting EED Binding Pocket.

2020

Abstract: The Polycomb Repressive complex 2 (PRC2) maintains a repressive chromatin state and silences many genes, acting as methylase on histone tails. This enzyme was found overexpressed in many types of cancer. In this work, we have set up a Computer-Aided Drug Design approach based on the allosteric modulation of PRC2. In order to minimize the possible bias derived from using a single set of coordinates within the protein-ligand complex, a dynamic workflow was developed. In details, molecular dynamic was used as tool to identify the most significant ligand-protein interactions from several crystallized protein structures. The identified features were used for the creation of dynamic pha…

Computer scienceAllosteric regulationBinding pocketmacromolecular substancesComputational biologyMolecular Dynamics SimulationLigands01 natural sciences03 medical and health sciencesProtein structureStructural BiologyDrug DiscoveryHumans030304 developmental biologyEED0303 health sciencesVirtual screeningBinding SitesbiologyOrganic ChemistryMolecular DynamicPolycomb Repressive Complex 2Dynamic pharmacophorePRC20104 chemical sciencesComputer Science ApplicationsChromatinMolecular Docking Simulation010404 medicinal & biomolecular chemistryROC CurveDocking (molecular)Drug Designbiology.proteinMolecular MedicinePharmacophorePRC2Allosteric SiteProtein BindingMolecular informaticsReferences
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CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification

2020

Abstract Background Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization. Interestingly, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using DNA sequence as input data. Results In this work, we propose CORENup, a deep learning model for nucleosome identification. CORENup processes a DNA sequence as input using one-hot representation and combines in a parallel fashion a fully convolutional neural network and a recurrent layer. These two parallel …

Computer scienceCelllcsh:Computer applications to medicine. Medical informaticsBiochemistryConvolutional neural networkDNA sequencingchemistry.chemical_compoundStructural BiologyTranscription (biology)medicineHumansNucleosomeA-DNAEpigeneticsMolecular Biologylcsh:QH301-705.5Nucleosome classificationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabiologybusiness.industryApplied MathematicsDeep learningResearchEpigeneticPattern recognitionGenomicsbiology.organism_classificationNucleosomesComputer Science ApplicationsRecurrent neural networkmedicine.anatomical_structurechemistrylcsh:Biology (General)Recurrent neural networkslcsh:R858-859.7Deep learning networksEukaryoteNeural Networks ComputerArtificial intelligenceDNA microarraybusinessDNABMC Bioinformatics
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PVAmpliconFinder: a workflow for the identification of human papillomaviruses from high-throughput amplicon sequencing

2019

Abstract Background The detection of known human papillomaviruses (PVs) from targeted wet-lab approaches has traditionally used PCR-based methods coupled with Sanger sequencing. With the introduction of next-generation sequencing (NGS), these approaches can be revisited to integrate the sequencing power of NGS. Although computational tools have been developed for metagenomic approaches to search for known or novel viruses in NGS data, no appropriate tool is available for the classification and identification of novel viral sequences from data produced by amplicon-based methods. Results We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify kno…

Computer scienceComputational biologylcsh:Computer applications to medicine. Medical informaticsBiochemistryWorkflowUser-Computer Interface03 medical and health sciencessymbols.namesakeStructural BiologyHumansVirus discoverylcsh:QH301-705.5PapillomaviridaeMolecular BiologyThroughput (business)PhylogenyAmplicon sequencing030304 developmental biologySanger sequencing0303 health sciencesBiological data030306 microbiologyMethodology ArticleApplied MathematicsHigh-Throughput Nucleotide SequencingPapillomavirusAmpliconComputer Science ApplicationsIdentification (information)Workflowlcsh:Biology (General)MetagenomicsDNA ViralAmplicon sequencingsymbolslcsh:R858-859.7Primer (molecular biology)DNA microarrayBMC Bioinformatics
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A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …

2013

Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…

Computer sciencecomputer.software_genreBiochemistrysymbols.namesakeDiscriminative modelStructural BiologyCluster AnalysisRelevance (information retrieval)Cluster analysisMolecular BiologyOligonucleotide Array Sequence AnalysisClustering discriminative ability of a distance function external validation indicesSettore INF/01 - InformaticaResearchApplied MathematicsMutual informationPearson product-moment correlation coefficientComputer Science ApplicationsHierarchical clusteringEuclidean distanceRange (mathematics)Metric (mathematics)symbolsData miningTranscriptomecomputerAlgorithmsBMC Bioinformatics
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A Large-Scale Empirical Evaluation of Cross-Validation and External Test Set Validation in (Q)SAR.

2013

(Q)SAR model validation is essential to ensure the quality of inferred models and to indicate future model predictivity on unseen compounds. Proper validation is also one of the requirements of regulatory authorities in order to accept the (Q)SAR model, and to approve its use in real world scenarios as alternative testing method. However, at the same time, the question of how to validate a (Q)SAR model, in particular whether to employ variants of cross-validation or external test set validation, is still under discussion. In this paper, we empirically compare a k-fold cross-validation with external test set validation. To this end we introduce a workflow allowing to realistically simulate t…

Computer sciencemedia_common.quotation_subjectOrganic ChemistryScale (descriptive set theory)Variance (accounting)computer.software_genreCross-validationComputer Science ApplicationsModel validationWorkflowStructural BiologyCheminformaticsTest setDrug DiscoveryMolecular MedicineQuality (business)Data miningcomputermedia_commonMolecular informatics
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What monomeric nucleotide binding domains can teach us about dimeric ABC proteins

2020

The classic conceptualization of ATP binding cassette (ABC) transporter function is an ATP-dependent conformational change coupled to transport of a substrate across a biological membrane via the transmembrane domains (TMDs). The binding of two ATP molecules within the transporter's two nucleotide binding domains (NBDs) induces their dimerization. Despite retaining the ability to bind nucleotides, isolated NBDs frequently fail to dimerize. ABC proteins without a TMD, for example ABCE and ABCF, have NBDs tethered via elaborate linkers, further supporting that NBD dimerization does not readily occur for isolated NBDs. Intriguingly, even in full-length transporters, the NBD-dimerized, outward-…

Conformational changeBiophysicsContext (language use)ATP-binding cassette transporterBiochemistry03 medical and health sciencesAdenosine TriphosphateProtein DomainsStructural BiologyGeneticsAnimalsHumansNucleotideMolecular Biology030304 developmental biologychemistry.chemical_classification0303 health sciencesBinding Sites030302 biochemistry & molecular biologyTransporterBiological membraneCell BiologyTransmembrane domainchemistryCyclic nucleotide-binding domainBiophysicsATP-Binding Cassette Transporterslipids (amino acids peptides and proteins)Protein MultimerizationProtein BindingFEBS Letters
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A closer look at the cholesterol sensor

2002

Abstract Transport of the sterol regulatory element-binding protein (SREBP) cleavage-activating protein (SCAP)–SREBP complex from the endoplasmic reticulum (ER) to the Golgi is the central event mediating the cholesterol-feedback process in mammalian cells. A conformational change in SCAP is a crucial step; when cholesterol levels are high, the conformation of SCAP enables the SCAP–SREBP complex to associate with an insulin-induced gene (INSIG) retention protein in the ER. By contrast, when cholesterol levels are low, SCAP switches to a conformation that enables the dissociation of the retention protein and the association of SCAP–SREBP with COP II vesicles.

Conformational changeCholesterolEndoplasmic reticulumVesicleBiologyGolgi apparatusBiochemistrySterolSterol regulatory element-binding proteinCell biologysymbols.namesakechemistry.chemical_compoundBiochemistryStructural biologychemistrypolycyclic compoundssymbolslipids (amino acids peptides and proteins)Molecular BiologyTrends in Biochemical Sciences
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Interacting processes in protein coagulation

1999

A strong interest is currently focused on protein self-association and deposit. This usually involves conformational changes of the entire protein or of a fragment. It can occur even at low concentrations and is responsible for pathologies such as systemic amyloidosis, Alzheimer's and Prion diseases, and other neurodegenerative pathologies. Readily available proteins, exhibiting at low concentration self-association properties related to conformational changes, offer very convenient model systems capable of providing insight into this class of problems. Here we report experiments on bovine serum albumin, showing that the process of conformational change of this protein towards an intermedia…

Conformational changeIntermediate formbiologyChemistryBiochemistrySystemic amyloidosisProtein coagulationBiochemistryStructural Biologybiology.proteinCoagulation (water treatment)Bovine serum albuminMolecular BiologyVolume concentrationProteins: Structure, Function, and Genetics
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