Search results for " Maximum-likelihood"

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Structure and function of the vacuolar Ccc1/VIT1 family of iron transporters and its regulation in fungi

2020

Iron is an essential micronutrient for most living beings since it participates as a redox active cofactor in many biological processes including cellular respiration, lipid biosynthesis, DNA replication and repair, and ribosome biogenesis and recycling. However, when present in excess, iron can participate in Fenton reactions and generate reactive oxygen species that damage cells at the level of proteins, lipids and nucleic acids. Organisms have developed different molecular strategies to protect themselves against the harmful effects of high concentrations of iron. In the case of fungi and plants, detoxification mainly occurs by importing cytosolic iron into the vacuole through the Ccc1/V…

ISC Iron-sulfur lusterCS Consistency scoreCcc1Ribosome biogenesisVacuoleReview ArticleYRE Yap response elementsBiochemistryBiotecnologia0302 clinical medicineStructural BiologyCg Candida glabrata0303 health sciencesMAFFT Multiple Alignment using Fast Fourier TransformNRAMP Natural Resistance-Associated Macrophage ProteinbiologyVIT1ChemistryMBD Metal-binding domainPlantsComputer Science ApplicationsBiochemistry030220 oncology & carcinogenesisCRD Cysteine-rich domainEg Eucalyptus grandisIron detoxificationBiotechnologyCBC CCAAT-binding core complexlcsh:BiotechnologySaccharomyces cerevisiaeVTL Vacuolar iron transporter-likeBiophysicsVIT Vacuolar iron transporterbZIP basic leucine-zipper03 medical and health sciencesFongsLipid biosynthesislcsh:TP248.13-248.65GeneticsFe IronIron transportTranscription factor030304 developmental biologyComputingMethodologies_COMPUTERGRAPHICSBLOSUM BLOcks SUbstitution MatrixTMD Transmembrane domainML Maximum-likelihoodIron regulationDNA replicationFungibiology.organism_classificationYeastYeastMetabolic pathwayH HelixHap Heme activator proteinVacuoleROS Reactive oxygen speciesFerroComputational and Structural Biotechnology Journal
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Estimation of ordered response models with sample selection

2011

We introduce two new Stata commands for the estimation of an ordered response model with sample selection. The opsel command uses a standard maximum-likelihood approach to fit a parametric specification of the model where errors are assumed to follow a bivariate Gaussian distribution. The snpopsel command uses the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 363–390) to fit a semiparametric specification of the model where the bivariate density function of the errors is approximated by a Hermite polynomial expansion. The snpopsel command extends the set of Stata routines for semi-nonparametric estimation of discrete response models. Compared to the other semi-n…

EstimationSample selectionHermite polynomialsResponse modelComputer scienceEstimatorSettore SECS-P/05 - EconometriaProbability density functionBivariate analysisst0226 opsel opsel postestimation sneop sneop postestimation snp2 snp2 postestimation snp2s snp2s postestimation snpopsel snpopsel postestimation snp snp postestimation ordered response models sample selection parametric maximum-likelihood estimation semi-nonparametric estimationSet (abstract data type)Mathematics (miscellaneous)StatisticsSettore SECS-P/01 - Economia PoliticaAlgorithmMathematicsParametric statistics
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