Search results for "SIMILARITY"

showing 10 items of 474 documents

Early farmers from across Europe directly descended from Neolithic Aegeans

2015

WOS: 000378272400038

0301 basic medicineMediterranean climatePopulation03 medical and health sciences0302 clinical medicineGenetic similarityddc:590Humans0601 history and archaeologyAnatoliaNeolithiceducationQH426HoloceneMesolithic030304 developmental biology2. Zero hungerPrincipal Component Analysis0303 health scienceseducation.field_of_studyMultidisciplinary060102 archaeologyGreeceMediterranean RegionEcologybusiness.industrySedentismAgriculture06 humanities and the artsBiological SciencesCCCBEuropepaleogenomicsGenetics Population030104 developmental biologyGeographyAncient DNAPaleogenomicsAgricultureAnthropologyBiological dispersalbusiness030217 neurology & neurosurgeryMesolithic
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Alignment Free Dissimilarities for Nucleosome Classification

2016

Epigenetic mechanisms such as nucleosome positioning, histone modifications and DNA methylation play an important role in the regulation of cell type-specific gene activities, yet how epigenetic patterns are established and maintained remains poorly understood. Recent studies have shown a role of DNA sequences in recruitment of epigenetic regulators. For this reason, the use of more suitable similarities or dissimilarity between DNA sequences could help in the context of epigenetic studies. In particular, alignment-free dissimilarities have already been successfully applied to identify distinct sequence features that are associated with epigenetic patterns and to predict epigenomic profiles…

0301 basic medicineNearest neighbour classifiersKnn classifierSettore INF/01 - Informatica030102 biochemistry & molecular biologybiologyComputer scienceSpeech recognitionEpigeneticContext (language use)Computational biologyL-tuples03 medical and health sciences030104 developmental biologyHistoneSimilarity (network science)DNA methylationbiology.proteinNucleosomeEpigeneticsAlignment free DNA sequence dissimilaritiesk-mersNucleosome classificationEpigenomics
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Modeling Chronic Toxicity: A Comparison of Experimental Variability With (Q)SAR/Read-Across Predictions

2018

This study compares the accuracy of (Q)SAR/read-across predictions with the experimental variability of chronic lowest-observed-adverse-effect levels (LOAELs) from in vivo experiments. We could demonstrate that predictions of the lazy structure-activity relationships (lazar) algorithm within the applicability domain of the training data have the same variability as the experimental training data. Predictions with a lower similarity threshold (i.e., a larger distance from the applicability domain) are also significantly better than random guessing, but the errors to be expected are higher and a manual inspection of prediction results is highly recommended.

0301 basic medicinePharmacologyTraining setlazarbusiness.industrylcsh:RM1-950Pattern recognition010501 environmental sciences01 natural sciencesexperimental variability(Q)SAR03 medical and health sciences030104 developmental biologylcsh:Therapeutics. PharmacologySimilarity (network science)Pharmacology (medical)Artificial intelligencebusinessChronic toxicityLOAEL0105 earth and related environmental sciencesApplicability domainMathematicsread-acrossFrontiers in Pharmacology
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FastaHerder2: Four Ways to Research Protein Function and Evolution with Clustering and Clustered Databases.

2016

The accelerated growth of protein databases offers great possibilities for the study of protein function using sequence similarity and conservation. However, the huge number of sequences deposited in these databases requires new ways of analyzing and organizing the data. It is necessary to group the many very similar sequences, creating clusters with automated derived annotations useful to understand their function, evolution, and level of experimental evidence. We developed an algorithm called FastaHerder2, which can cluster any protein database, putting together very similar protein sequences based on near-full-length similarity and/or high threshold of sequence identity. We compressed 50…

0301 basic medicineProtein structure databaseProteomicsProteomeSequence analysisComputer sciencecomputer.software_genreSensitivity and SpecificitySet (abstract data type)Evolution Molecular03 medical and health sciences0302 clinical medicineSimilarity (network science)Sequence Analysis ProteinGeneticsCluster (physics)AnimalsCluster AnalysisHumansCluster analysisDatabases ProteinMolecular BiologySequenceDatabaseFunction (mathematics)Computational Mathematics030104 developmental biologyComputational Theory and MathematicsModeling and SimulationData miningcomputer030217 neurology & neurosurgerySoftwareJournal of computational biology : a journal of computational molecular cell biology
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Innovative Strategies to Develop Chemical Categories Using a Combination of Structural and Toxicological Properties.

2016

Interest is increasing in the development of non-animal methods for toxicological evaluations. These methods are however, particularly challenging for complex toxicological endpoints such as repeated dose toxicity. European Legislation, e.g., the European Union's Cosmetic Directive and REACH, demands the use of alternative methods. Frameworks, such as the Read-across Assessment Framework or the Adverse Outcome Pathway Knowledge Base, support the development of these methods. The aim of the project presented in this publication was to develop substance categories for a read-across with complex endpoints of toxicity based on existing databases. The basic conceptual approach was to combine str…

0301 basic medicineQuantitative structure–activity relationshipread acrossPredictive Clustering Tree (PCT) methodComputer science610010501 environmental sciencescomputer.software_genre600 Technik Medizin angewandte Wissenschaften::610 Medizin und Gesundheit01 natural sciences03 medical and health sciencesPharmacology (medical)Cluster analysis0105 earth and related environmental sciencesOriginal ResearchAlternative methodsPharmacologytoxicological and structural similaritybusiness.industryQSARlcsh:RM1-950non-animal methods; QSAR; readacross; Predictive Clustering Tree (PCT) method; toxicological and structural similarityIdentification (information)Tree (data structure)030104 developmental biologyConceptual approachlcsh:Therapeutics. PharmacologyKnowledge basenon-animal methodsData miningWeb servicebusinesscomputerFrontiers in pharmacology
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Retrieving infinite numbers of patterns in a spin-glass model of immune networks

2013

The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…

0301 basic medicineSimilarity (geometry)Spin glassComputer sciencestatistical mechanicFOS: Physical sciencesGeneral Physics and AstronomyNetwork topologyTopology01 natural sciencesQuantitative Biology::Cell Behavior03 medical and health sciencesCell Behavior (q-bio.CB)0103 physical sciencesattractor neural-networks; statistical mechanics; brain networks; Physics and Astronomy (all)Physics - Biological Physics010306 general physicsAssociative propertybrain networkArtificial neural networkMechanism (biology)ErgodicityDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksAcquired immune system030104 developmental biologyBiological Physics (physics.bio-ph)FOS: Biological sciencesattractor neural-networkQuantitative Biology - Cell Behavior
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Gene-based and semantic structure of the Gene Ontology as a complex network

2012

The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. This approach might be usefully complemented by a bottom-up approach based on the knowledge of relationships amongst genes. To this end, we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium and a gene-based …

0301 basic medicineStatistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComplex systemComputer scienceMolecular Networks (q-bio.MN)Complex systemFOS: Physical sciencesNetworkCondensed Matter PhysicPhysics and Society (physics.soc-ph)computer.software_genreQuantitative Biology - Quantitative MethodsStatistics - ApplicationsGeneSemantic network03 medical and health sciencesSemantic similarityQuantitative Biology - Molecular NetworksApplications (stat.AP)GeneQuantitative Methods (q-bio.QM)Community detectionGene ontologybusiness.industryOntologyOntology-based data integrationComplex networkCondensed Matter PhysicsBipartite system030104 developmental biologyBipartite system; Community detection; Complex systems; Genes; Networks; Ontology; Condensed Matter Physics; Statistics and ProbabilityFOS: Biological sciencesOntologyWeighted networkData miningArtificial intelligenceComputingMethodologies_GENERALbusinesscomputerNatural language processing
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Discovery of Natural Products as Novel and Potent FXR Antagonists by Virtual Screening

2018

Farnesoid X receptor (FXR) is a member of nuclear receptor family involved in multiple physiological processes through regulating specific target genes. The critical role of FXR as a transcriptional regulator makes it a promising target for diverse diseases, especially those related to metabolic disorders such as diabetes and cholestasis. However, the underlying activation mechanism of FXR is still a blur owing to the absence of proper FXR modulators. To identify potential FXR modulators, an in-house natural product database (NPD) containing over 4,000 compounds was screened by structure-based virtual screening strategy and subsequent hit-based similarity searching method. After the yeast t…

0301 basic medicinenatural product01 natural scienceslcsh:Chemistry03 medical and health scienceschemistry.chemical_compoundTranscriptional regulationGeneIC50Original ResearchVirtual screeningNatural productantagonistmolecular dockingsimilarity searchingGeneral Chemistryvirtual screening0104 chemical sciencesChemistry010404 medicinal & biomolecular chemistry030104 developmental biologyFXRlcsh:QD1-999Nuclear receptorBiochemistrychemistryFarnesoid X receptorGuggulsteroneFrontiers in Chemistry
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A comparison between nine laboratories performing triangle tests

2012

WOS: 000299451400001; International audience; Fifteen groups of participants in nine laboratories performed triangle tests with two pairs of soft drinks. Groups differed in practice level with triangle tests: eight groups of 60 consumers who were not used to triangle test, three groups of qualified assessors who have already performed a few triangle tests, and four groups of trained assessors with a more extensive practice of triangle tests; qualified and trained groups included 9 or 18 assessors. The soft drinks were made from syrups at two levels of dilution in order to achieve about 55% of correct responses to test for difference and about 40% of correct responses to test for similarity.…

030309 nutrition & dietetics[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritioneducationTriangle testmemorytaste03 medical and health sciences0404 agricultural biotechnologypreference testsSimilarity (network science)StatisticsConsumer groupSimilarity testMathematicsbeta-binomial model0303 health sciencesNutrition and Dieteticsreplicated differenceSignificant differenceoverdispersion04 agricultural and veterinary sciencessensory difference testswarm-up040401 food scienceTest (assessment)Difference testexpertiseConsumersSimilarity testSelected assessors[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood ScienceTriangle test
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Perceived similarity between written Estonian and Finnish : Strings of letters or morphological units?

2017

The distance or similarity between two languages can be objective or actual, i.e. discoverable by the tools and methods of linguists, or perceived by users of the languages. In this article two methods, the Levenshtein Distance (LD), which purports to measure the objective distance, and the Index of Perceived Similarity (IPS), which quantifies language users’ perceptions, are compared. The data are the quantitative results of a test measuring conscious perceptions of similarity between Estonian and Finnish inflectional morphology by Finnish and Estonian native speakers (‘Finns’ and ‘Estonians’) with no knowledge of and exposure to the other (‘target’) language. The results show that Finns s…

060201 languages & linguisticsmeasuring actual and perceived cross-linguistic similarityLinguistics and Languagemedia_common.quotation_subjectFinnishta612106 humanities and the artsEstonianLevenshtein distanceEstonianLanguage and LinguisticsLinguisticslanguage.human_languageTest (assessment)Similarity (network science)Perception0602 languages and literaturelanguageinflectional morphologyPsychologymedia_commonNordic Journal of Linguistics
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