Search results for "Bioinformatic"

showing 10 items of 1651 documents

In Silico Prediction of Caco-2 Cell Permeability by a Classification QSAR Approach

2011

In the present study, 21 validated QSAR models that discriminate compounds with high Caco-2 permeability (Papp ≥8×10(-6)  cm/s) from those with moderate-poor permeability (Papp <8×10(-6)  cm/s) were developed on a novel large dataset of 674 compounds. 20 DRAGON descriptor families were used. The global accuracies of obtained models were ranking between 78-82 %. A general model combining all types of molecular descriptors was developed and it classified correctly 81.56 % and 83.94 % for training and test sets, respectively. An external set of 10 compounds was predicted and 80 % was correctly assessed by in vitro Caco-2 assays. The potential use of the final model was evaluated by a virtual s…

Virtual screeningQuantitative structure–activity relationshipIn silicoOrganic ChemistryComputational biologyBiologyBioinformaticsComputer Science ApplicationsStructural BiologyMolecular descriptorDrug DiscoveryHuman intestinal absorptionMolecular MedicineCell permeabilityMolecular Informatics
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Visceral Adiposity Index: An Indicator of Adipose Tissue Dysfunction

2013

The Visceral Adiposity Index (VAI) has recently proven to be an indicator of adipose distribution and function that indirectly expresses cardiometabolic risk. In addition, VAI has been proposed as a useful tool for early detection of a condition of cardiometabolic risk before it develops into an overt metabolic syndrome. The application of the VAI in particular populations of patients (women with polycystic ovary syndrome, patients with acromegaly, patients with NAFLD/NASH, patients with HCV hepatitis, patients with type 2 diabetes, and general population) has produced interesting results, which have led to the hypothesis that the VAI could be considered a marker of adipose tissue dysfuncti…

Visceral Adiposity Indexeducation.field_of_studyPathologymedicine.medical_specialtylcsh:RC648-665Endocrine and Autonomic Systemsbusiness.industryEndocrinology Diabetes and MetabolismPopulationAdipose tissueType 2 diabetesReview ArticleBioinformaticsmedicine.diseaselcsh:Diseases of the endocrine glands. Clinical endocrinologyPolycystic ovaryEndocrinologyHcv hepatitisAcromegalyMedicineMetabolic syndromebusinesseducationProspective cohort study
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Distance measures for biological sequences: Some recent approaches

2008

AbstractSequence comparison has become a very essential tool in modern molecular biology. In fact, in biomolecular sequences high similarity usually implies significant functional or structural similarity. Traditional approaches use techniques that are based on sequence alignment able to measure character level differences. However, the recent developments of whole genome sequencing technology give rise to need of similarity measures able to capture the rearrangements involving large segments contained in the sequences. This paper is devoted to illustrate different methods recently introduced for the alignment-free comparison of biological sequences. Goal of the paper is both to highlight t…

Whole genome sequencingComputer sciencebusiness.industryApplied MathematicsSequence alignmentMachine learningcomputer.software_genreBioinformaticsMeasure (mathematics)GenomeDistance measuresSimilitudeTheoretical Computer ScienceArtificial IntelligenceSimilarity (psychology)Metric (mathematics)Artificial intelligencebusinesscomputerSoftwareInternational Journal of Approximate Reasoning
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Mammalian cell metabolomics: Experimental design and sample preparation

2013

Metabolomics represents the global assessment of metabolites in a biological sample and reports the closest information to the phenotype of the biological system under study. Mammalian cell metabolomics has emerged as a promising tool with potential applications in many biotechnology and research areas. Metabolomics workflow includes experimental design, sampling, sample processing, metabolite analysis, and data processing. Given their influence on metabolite content and biological interpretation of data, a good experimental design and the appropriate choice of a sample processing method are prerequisites for success in any metabolomic study. The use of mammalian cells in the metabolomics f…

WorkflowMetabolomicsResearch areasMammalian cellClinical BiochemistrySample processingSample preparationComputational biologyMetabolite analysisBiologyBioinformaticsBiochemistryAnalytical ChemistryELECTROPHORESIS
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Real-time 3D TUG test movement analysis for balance assessment using Microsoft Kinect

2014

International audience

[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM][INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]ComputingMilieux_MISCELLANEOUS[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
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Analyse cinématique des caractéristiques de planifications motrices chez les personnes âgées fragiles

2015

International audience

[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM][INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]ComputingMilieux_MISCELLANEOUS[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
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Insights into genome plasticity of the wine-making bacterium Oenococcus oeni strain ATCC BAA-1163 by decryption of its whole genome.

2008

International audience; Studying genomes of O. oeni strains having opposite oenological aptitudes is important for understanding why this lactic acid bacterium involved in malolactic fermentation is so well adapted to wine. Here, the genome of a strain ATCC BAA-1163, is described and compared with the recently reported genome of the better wine-adapted strain PSU-1. The BAA-1163 genome (8X) was obtained by shotgun sequencing and Phrap assembling. Compact and 62% AT-rich, it consists of a circular 1,792,103-bp chromosome and a 3,948-bp plasmid. It was analysed through a CAAT-Box annotation platform and manually inspected. A total of 51 RNA genes were detected, including two rRNA operons (the…

[ SDV.BID.EVO ] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE][SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM][SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE][SDV.BID.EVO] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE][ SDV.MP.BAC ] Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][SDV.MP.BAC] Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology[ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
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Numerical models contribute to expand the sweet taste chemical space

2021

[CHIM.THEO] Chemical Sciences/Theoretical and/or physical chemistry[CHIM] Chemical Sciences[CHIM.CHEM] Chemical Sciences/Cheminformatics[SDV.BBM] Life Sciences [q-bio]/Biochemistry Molecular Biology[SDV.BBM.BP] Life Sciences [q-bio]/Biochemistry Molecular Biology/Biophysics[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC][STAT.ML] Statistics [stat]/Machine Learning [stat.ML][INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
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Optimisation et implémentation de méthodes bio-inspirées d'extraction de caractéristiques pour la reconnaissance d'objets visuels

2016

Industry has growing needs for so-called “intelligent systems”, capable of not only ac-quire data, but also to analyse it and to make decisions accordingly. Such systems areparticularly useful for video-surveillance, in which case alarms must be raised in case ofan intrusion. For cost saving and power consumption reasons, it is better to perform thatprocess as close to the sensor as possible. To address that issue, a promising approach isto use bio-inspired frameworks, which consist in applying computational biology modelsto industrial applications. The work carried out during that thesis consisted in select-ing bio-inspired feature extraction frameworks, and to optimize them with the aim t…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Bio-inspiréApprentissage automatiqueIntelligence artificielle[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Descripteurs[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]EmbarquéAlgorithm-architecture matching[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM]Vision par ordinateurMachine learningRéseaux de neuronesComputer vision[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]OptimisationsFPGANeural networks[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
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Whole mirror duplication-random loss model and pattern avoiding permutations

2010

International audience; In this paper we study the problem of the whole mirror duplication-random loss model in terms of pattern avoiding permutations. We prove that the class of permutations obtained with this model after a given number p of duplications of the identity is the class of permutations avoiding the alternating permutations of length p2+1. We also compute the number of duplications necessary and sufficient to obtain any permutation of length n. We provide two efficient algorithms to reconstitute a possible scenario of whole mirror duplications from identity to any permutation of length n. One of them uses the well-known binary reflected Gray code (Gray, 1953). Other relative mo…

[INFO.INFO-CC]Computer Science [cs]/Computational Complexity [cs.CC]Class (set theory)0206 medical engineeringBinary number0102 computer and information sciences02 engineering and technology[ MATH.MATH-CO ] Mathematics [math]/Combinatorics [math.CO]01 natural sciencesIdentity (music)Combinatorial problemsTheoretical Computer ScienceGray codeCombinatoricsPermutation[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM]Gene duplicationRandom loss[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]Pattern avoiding permutationGenerating algorithmComputingMilieux_MISCELLANEOUSMathematicsDiscrete mathematicsWhole duplication-random loss modelMathematics::CombinatoricsGenomeParity of a permutationComputer Science Applications[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO][ INFO.INFO-CC ] Computer Science [cs]/Computational Complexity [cs.CC]Binary reflected Gray code010201 computation theory & mathematicsSignal Processing[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]020602 bioinformaticsAlgorithmsInformation Systems
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