Search results for "Database"

showing 10 items of 2136 documents

LASS6, an additional member of the longevity assurance gene family

2005

Longevity assurance genes (LAGs) represent a subgroup of the homeobox gene family. Five mammalian homologs have been reported, and the corresponding proteins have previously been investigated with respect to their key role in ceramide synthesis. However, members of the LAG family have been shown to be involved in cell growth regulation and cancer differentiation. In an effort to characterize additional members of the LAG family, we have screened the latest releases of genomic databases and report on the bioinformatic characterization of yet another member, LAG1 longevity assurance homolog 6 (LASS6). Like other LAG family members, the LASS6 protein contained a homeodomain and LAG1 domain. In…

Protein familyProtein ConformationIn silicoLongevityMolecular Sequence DataBiologyHomology (biology)MiceDatabases GeneticSphingosine N-AcyltransferaseGeneticsAnimalsHumansGene familyAmino Acid SequenceGeneZebrafishPhylogenyZebrafishHomeodomain ProteinsGeneticsBase SequenceGenome HumanMicroarray analysis techniquesGenes HomeoboxMembrane ProteinsGeneral Medicinebiology.organism_classificationRatsChromosomes Human Pair 2HomeoboxInternational Journal of Molecular Medicine
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Bioinformatic flowchart and database to investigate the origins and diversity of Clan AA peptidases

2009

Abstract Background Clan AA of aspartic peptidases relates the family of pepsin monomers evolutionarily with all dimeric peptidases encoded by eukaryotic LTR retroelements. Recent findings describing various pools of single-domain nonviral host peptidases, in prokaryotes and eukaryotes, indicate that the diversity of clan AA is larger than previously thought. The ensuing approach to investigate this enzyme group is by studying its phylogeny. However, clan AA is a difficult case to study due to the low similarity and different rates of evolution. This work is an ongoing attempt to investigate the different clan AA families to understand the cause of their diversity. Results In this paper, we…

Protein familySequence analysisImmunologyProtein domainMolecular Sequence DataBiologycomputer.software_genreGeneral Biochemistry Genetics and Molecular BiologyProtein Structure SecondaryPhylogeneticsSequence Analysis ProteinSoftware DesignConsensus SequenceConsensus sequenceAspartic Acid EndopeptidasesClanAmino Acid SequenceDatabases ProteinPeptide sequencelcsh:QH301-705.5Ecology Evolution Behavior and SystematicsPhylogenyDatabaseAgricultural and Biological Sciences(all)Biochemistry Genetics and Molecular Biology(all)Applied MathematicsResearchComputational BiologyGenetic VariationGene AnnotationTemplates GeneticMarkov ChainsProtein Structure Tertiarylcsh:Biology (General)Modeling and SimulationGeneral Agricultural and Biological SciencescomputerBiology Direct
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Extracting similar sub-graphs across PPI Networks

2009

Singling out conserved modules (corresponding to connected sub-graphs) throughout protein-protein interaction networks of different organisms is a main issue in bioinformatics because of its potential applications in biology. This paper presents a method to discover highly matching sub-graphs in such networks. Sub-graph extraction is carried out by taking into account, on the one side, both protein sequence and network structure similarities and, on the other side, both quantitative and reliability information possibly available about interactions. The method is conceived as a generalization of a known technique, able to discover functional orthologs in interaction networks. Some preliminar…

Protein structure databaseBioinformatics network analysisProtein sequencingMatching (graph theory)GeneralizationComputer scienceReliability (computer networking)Protein function predictionGraph theoryData miningcomputer.software_genrecomputerNetwork analysis
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A computer system to perform structure comparison using TOPS representations of protein structure

2001

We describe the design and implementation of a fast topology-based method for protein structure comparison. The approach uses the TOPS topological representation of protein structure, aligning two structures using a common discovered pattern and generating measure of distance derived from an insert score. Heavy use is made of a constraint-based pattern-matching algorithm for TOPS diagrams that we have designed and described elsewhere (Bioinformatics 15(4) (1999) 317). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with …

Protein structure databaseMeasure (data warehouse)Molecular StructureComputer scienceGeneral Chemical EngineeringProteinsSequence Homologycomputer.file_formatTOPSProtein structure predictioncomputer.software_genreProtein Data BankApplied Microbiology and BiotechnologyPattern Recognition AutomatedArtificial IntelligencePattern matchingData miningProtein topologyRepresentation (mathematics)computerAlgorithmsSoftwareBiotechnology
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Experimental Evaluation of Protein Secondary Structure Predictors

2009

Understanding protein biological function is a key issue in modern biology, which is largely determined by its 3D shape. Protein 3D shape, in its turn, is functionally implied by its amino acid sequence. Since the direct inspection of such 3D structures is rather expensive and time consuming, a number of software techniques have been developed in the last few years that predict a spatial model, either of the secondary or of the tertiary form, for a given target protein starting from its amino acid sequence. This paper offers a comparison of several available automatic secondary structure prediction tools. The comparison is of the experimental kind, where two relevant sets of proteins, a non…

Protein structure databasebusiness.industryProtein structure predictionBioinformaticsMachine learningcomputer.software_genreSet (abstract data type)Bioinformatics Protein PredictionTest caseGlobal distance testArtificial intelligenceCASPbusinessPeptide sequencecomputerProtein secondary structure
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Toward completion of the Earth’s proteome: an update a decade later

2017

Protein databases are steadily growing driven by the spread of new more efficient sequencing techniques. This growth is dominated by an increase in redundancy (homologous proteins with various degrees of sequence similarity) and by the incapability to process and curate sequence entries as fast as they are created. To understand these trends and aid bioinformatic resources that might be compromised by the increasing size of the protein sequence databases, we have created a less-redundant protein data set. In parallel, we analyzed the evolution of protein sequence databases in terms of size and redundancy. While the SwissProt database has decelerated its growth mostly because of a focus on i…

ProteomeOperations researchKnowledge Bases0206 medical engineering02 engineering and technologyComputational biologyBiology03 medical and health sciencesAnnotationProtein sequencingSequence Analysis ProteinThree-domain systemRedundancy (engineering)AnimalsHumansDatabases ProteinMolecular Biology030304 developmental biologySequence (medicine)0303 health sciencesComputational BiologyProteinsProtein superfamilyProteomeUniProtSoftware020602 bioinformaticsInformation SystemsBriefings in Bioinformatics
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Assessing the low complexity of protein sequences via the low complexity triangle.

2020

Background Proteins with low complexity regions (LCRs) have atypical sequence and structural features. Their amino acid composition varies from the expected, determined proteome-wise, and they do not follow the rules of structural folding that prevail in globular regions. One way to characterize these regions is by assessing the repeatability of a sequence, that is, calculating the local propensity of a region to be part of a repeat. Results We combine two local measures of low complexity, repeatability (using the RES algorithm) and fraction of the most frequent amino acid, to evaluate different proteomes, datasets of protein regions with specific features, and individual cases of proteins…

ProteomeProteomesComputer scienceProtein SequencingBiochemistryDatabase and Informatics MethodsSequence Analysis ProteinProtein methodsPeptide sequencechemistry.chemical_classification0303 health sciencesSequenceMultidisciplinary030302 biochemistry & molecular biologyQRGenomicsAmino acidTandem RepeatsProteomeAmino Acid AnalysisMedicineSequence AnalysisResearch ArticleRepetitive Sequences Amino AcidBioinformaticsSequence analysisScienceResearch and Analysis MethodsGenome Complexity03 medical and health sciencesProtein DomainsAmino Acid Sequence AnalysisTandem repeatGeneticsHumansFraction (mathematics)Repeated SequencesAmino Acid SequenceMolecular Biology TechniquesSequencing TechniquesRepresentation (mathematics)Molecular Biology030304 developmental biologyMolecular Biology Assays and Analysis Techniquesbusiness.industryBiology and Life SciencesProteinsComputational BiologyPattern recognitionchemistryGlobular ProteinsArtificial intelligencebusinessPLoS ONE
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Identification of Prostate-Enriched Proteins by In-depth Proteomic Analyses of Expressed Prostatic Secretions in Urine

2012

Urinary expressed prostatic secretion or "EPS-urine" is proximal tissue fluid that is collected after a digital rectal exam (DRE). EPS-urine is a rich source of prostate-derived proteins that can be used for biomarker discovery for prostate cancer (PCa) and other prostatic diseases. We previously conducted a comprehensive proteome analysis of direct expressed prostatic secretions (EPS). In the current study, we defined the proteome of EPS-urine employing Multidimensional Protein Identification Technology (MudPIT) and providing a comprehensive catalogue of this body fluid for future biomarker studies. We identified 1022 unique proteins in a heterogeneous cohort of 11 EPS-urines derived from …

Proteomics prostate cancer expressed prostatic secretions urineMaleProteomicsProstatic DiseasesProteomeProstatic Secretory ProteinsHuman Protein AtlasComputational biologyProstatic DiseasesBiologyProteomicsBioinformaticsBiochemistryArticleMass SpectrometryProstate cancerSettore BIO/13 - Biologia ApplicataProstatemedicineHumansBiomarker discoveryDatabases ProteinChromatography High Pressure LiquidGene Expression ProfilingProstateProstatic NeoplasmsProstatic Secretory ProteinsReproducibility of ResultsGeneral Chemistrymedicine.diseasemedicine.anatomical_structureCase-Control StudiesProteomeJournal of Proteome Research
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Metaproteomic analysis of atmospheric aerosol samples.

2016

Metaproteomic analysis of air particulate matter provides information about the abundance and properties of bioaerosols in the atmosphere and their influence on climate and public health. We developed and applied efficient methods for the extraction and analysis of proteins from glass fiber filter samples of total, coarse, and fine particulate matter. Size exclusion chromatography was applied to remove matrix components, and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was applied for protein fractionation according to molecular size, followed by in-gel digestion and LC-MS/MS analysis of peptides using a hybrid Quadrupole-Orbitrap MS. Maxquant software and the Swiss-…

Proteomics010504 meteorology & atmospheric sciencesSize-exclusion chromatographyIndoor bioaerosolFractionation010501 environmental sciences01 natural sciencesBiochemistryAnalytical ChemistryMatrix (chemical analysis)Fungal ProteinsBacterial ProteinsMetaproteomicsTandem Mass SpectrometryDatabases ProteinChromatography High Pressure Liquid0105 earth and related environmental sciencesPlant ProteinsAerosolsFungal proteinAir PollutantsChromatographyMass spectrometryChemistryAtmosphereProteinsParticulatesAllergensAtmospheric aerosolsAerosolEnvironmental chemistryBioanalytical methodsParticleElectrophoresis Polyacrylamide GelParticulate MatterHPLCResearch PaperAnalytical and bioanalytical chemistry
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A proteomic approach to studying plant response to crenate broomrape (Orobanche crenata) in pea (Pisum sativum)

2004

Abstract Crenate broomrape ( Orobanche crenata ) is a parasitic plant that threatens legume production in Mediterranean areas. Pea ( Pisum sativum ) is severely affected, and only moderate levels of genetic resistance have so far been identified. In the present work we selected the most resistant accession available (Ps 624) and compared it with a susceptible (Messire) cultivar. Experiments were performed by using pot and Petri dish bioassays, showing little differences in the percentage of broomrape seed germination induced by both genotypes, but a significant hamper in the number of successfully installed tubercles and their developmental stage in the Ps 624 compared to Messire. The prote…

Proteomics0106 biological sciencesSilver StainingGenotypeParasitic plantNitrogen assimilationGene ExpressionPlant ScienceHorticultureOrobanche crenataPeptide MappingPlant Roots01 natural sciencesBiochemistryFructokinasePisum03 medical and health sciencesSativumGlutamine synthetaseElectrophoresis Gel Two-DimensionalDatabases ProteinMolecular Biology[SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyComputingMilieux_MISCELLANEOUSPlant Proteins030304 developmental biologyPathogenesis-related protein2. Zero hunger0303 health sciencesbiologyOrobanchePeasGeneral Medicinebiology.organism_classification[SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyBiochemistrySpectrometry Mass Matrix-Assisted Laser Desorption-IonizationElectrophoresis Polyacrylamide Gel010606 plant biology & botany
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