cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1276549.v1
title: Regulation of MAP kinase signaling cascade by microRNAs in <i>Oryza sativa</i>

description: Mitogen activated protein kinase (MAPK) pathway is one of the most conserved signaling cascade in plants regulating a plethora of cellular processes including normal growth and development, abiotic and biotic stress responses. The perception of external cues triggers the phosphorylation of three tier MAPKKK-MAPKK-MAPK cascade which finally modifies a downstream substrate thereby regulating the cellular processes. Whereas, the transcription regulation by MAPKs, mediated through their substrates is well studied in plants, the transcription and post-transcriptional regulation of the MAPK genes are poorly understood. Previous studies from the animals systems suggested the miRNAs regulate the post-transcriptional regulation of MAPK transcripts. Here we attempt to unravel the post-transcriptional regulation of MAPKs by miRNAs in model crop plant <i>Oryza sativa</i>. Using <i>in silico</i> tools, we predict the miRNAs for 98 out of 99 MAPK transcripts. The predicted miRNAs were validated for the biological relevance of their function. The inverse correlation between relative transcript levels between the MAPKs and their predicted miRNAs validated the <i>in silico</i> prediction. Taken together, this report demonstrates the significance of miRNAs in regulation of the MAPK pathway in plants with a new direction to study the plant signaling molecules.
DOI: 10.6084/m9.figshare.1276481
title: Precise Measurement of the Thickness of a Dielectric Layer on a Metal Surface by Use of a Modified Otto Optical Configuration

description: We propose a modified method for thickness measurement of a dielectric coating layer on metal based on Otto optical configuration (O-configuration). This method enables us to estimate the coating thickness that typically ranges from several tens of nanometers to more than one micrometer with precision less than a few nanometers. The common method to measure the thickness of dielectric coating layer is to utilize the frustrated total-internal reflection. In order to measure the thickness of several tens of nanometers, one can apply the surface-plasmon-resonance (SPR) phenomenon generated by the p-polarized light. For thickness larger than one hundred nanometers, a metal-clad leaky-waveguide (MCLW) mode generated by the p- or the s-polarized light can be employed without significant changes to the optical setup. The numerical and experimental verifications of the modified O-configuration reveals its effectiveness for precise measurement of moderately-thick dielectric coating layer on the metal.
DOI: 10.6084/m9.figshare.1276473
title: Predictive properties of DNA methylation patterns in primary tumor samples for osteosarcoma relapse status

description: Osteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the <i>TLR4</i> gene demonstrates one of strongest associations between DNA methylation and 5 y event-free survival (<i>P</i>-value = 1.7 × 10<sup>−6</sup>), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has the potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.
DOI: 10.6084/m9.figshare.1276481.v2
title: Precise Measurement of the Thickness of a Dielectric Layer on a Metal Surface by Use of a Modified Otto Optical Configuration

description: We propose a modified method for thickness measurement of a dielectric coating layer on metal based on Otto optical configuration (O-configuration). This method enables us to estimate the coating thickness that typically ranges from several tens of nanometers to more than one micrometer with precision less than a few nanometers. The common method to measure the thickness of dielectric coating layer is to utilize the frustrated total-internal reflection. In order to measure the thickness of several tens of nanometers, one can apply the surface-plasmon-resonance (SPR) phenomenon generated by the p-polarized light. For thickness larger than one hundred nanometers, a metal-clad leaky-waveguide (MCLW) mode generated by the p- or the s-polarized light can be employed without significant changes to the optical setup. The numerical and experimental verifications of the modified O-configuration reveals its effectiveness for precise measurement of moderately-thick dielectric coating layer on the metal.
DOI: 10.6084/m9.figshare.1276481.v1
title: Precise Measurement of the Thickness of a Dielectric Layer on a Metal Surface by Use of a Modified Otto Optical Configuration

description: We propose a modified method for thickness measurement of a dielectric coating layer on metal based on Otto optical configuration (O-configuration). This method enables us to estimate the coating thickness that typically ranges from several tens of nanometers to more than one micrometer with precision less than a few nanometers. The common method to measure the thickness of dielectric coating layer is to utilize the frustrated total-internal reflection. In order to measure the thickness of several tens of nanometers, one can apply the surface-plasmon-resonance (SPR) phenomenon generated by the p-polarized light. For thickness larger than one hundred nanometers, a metal-clad leaky-waveguide (MCLW) mode generated by the p- or the s-polarized light can be employed without significant changes to the optical setup. The numerical and experimental verifications of the modified O-configuration reveals its effectiveness for precise measurement of moderately-thick dielectric coating layer on the metal.
DOI: 10.6084/m9.figshare.1276473.v1
title: Predictive Properties of DNA Methylation Patterns in Primary Tumor Samples for Osteosarcoma Relapse Status

description: ABSTRACTOsteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the <i>TLR4</i> gene demonstrates one of strongest associations between DNA methylation and five year event-free survival (p-value = 1.7 x10<sup>−6</sup>), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.
DOI: 10.6084/m9.figshare.1276473.v2
title: Predictive properties of DNA methylation patterns in primary tumor samples for osteosarcoma relapse status

description: Osteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the <i>TLR4</i> gene demonstrates one of strongest associations between DNA methylation and 5 y event-free survival (<i>P</i>-value = 1.7 × 10<sup>−6</sup>), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has the potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.
DOI: 10.6084/m9.figshare.1276473.v4
title: Predictive properties of DNA methylation patterns in primary tumor samples for osteosarcoma relapse status

description: Osteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the <i>TLR4</i> gene demonstrates one of strongest associations between DNA methylation and 5 y event-free survival (<i>P</i>-value = 1.7 × 10<sup>−6</sup>), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has the potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.
DOI: 10.6084/m9.figshare.1276473.v3
title: Predictive properties of DNA methylation patterns in primary tumor samples for osteosarcoma relapse status

description: Osteosarcoma is the most common primary malignant bone tumor in children. Validated biological markers for disease prognosis available at diagnosis are lacking. No genome-wide DNA methylation studies linked to clinical outcomes have been reported in osteosarcoma to the best of our knowledge. To address this, we tested the methylome at over 1.1 million loci in 15 osteosarcoma biopsy samples obtained prior to the initiation of therapy and correlated these molecular data with disease outcomes. At more than 17% of the tested loci, samples obtained from patients who experienced disease relapse were more methylated than those from patients who did not have recurrence while patients who did not experience disease relapse had more DNA methylation at fewer than 1%. In samples from patients who went on to have recurrent disease, increased DNA methylation was found at gene bodies, intergenic regions and empirically-annotated candidate enhancers, whereas candidate gene promoters were unusual for a more balanced distribution of increased and decreased DNA methylation with 6.6% of gene promoter loci being more methylated and 2% of promoter loci being less methylated in patients with disease relapse. A locus at the <i>TLR4</i> gene demonstrates one of strongest associations between DNA methylation and 5 y event-free survival (<i>P</i>-value = 1.7 × 10<sup>−6</sup>), with empirical annotation of this locus showing promoter characteristics. Our data indicate that DNA methylation information has the potential to be predictive of outcome in pediatric osteosarcoma, and that both promoters and non-promoter loci are potentially informative in DNA methylation studies.
DOI: 10.6084/m9.figshare.1276462
title: Dimension-Reduced Modeling of Spatio-Temporal Processes

description: The field of spatial and spatio-temporal statistics is increasingly faced with the challenge of very large datasets. The classical approach to spatial and spatio-temporal modeling is very computationally demanding when datasets are large, which has led to interest in methods that use dimension-reduction techniques. In this article, we focus on modeling of two spatio-temporal processes where the primary goal is to predict one process from the other and where datasets for both processes are large. We outline a general dimension-reduced Bayesian hierarchical modeling approach where spatial structures of both processes are modeled in terms of a low number of basis vectors, hence reducing the spatial dimension of the problem. Temporal evolution of the processes and their dependence is then modeled through the coefficients of the basis vectors. We present a new method of obtaining data-dependent basis vectors, which is geared toward the goal of predicting one process from the other. We apply these methods to a statistical downscaling example, where surface temperatures on a coarse grid over Antarctica are downscaled onto a finer grid. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1276459
title: Generalized Species Sampling Priors With Latent Beta Reinforcements

description: Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appropriate. We introduce a novel and probabilistically coherent family of nonexchangeable species sampling sequences characterized by a tractable predictive probability function with weights driven by a sequence of independent Beta random variables. We compare their theoretical clustering properties with those of the Dirichlet process and the two parameters Poisson–Dirichlet process. The proposed construction provides a complete characterization of the joint process, differently from existing work. We then propose the use of such process as prior distribution in a hierarchical Bayes’ modeling framework, and we describe a Markov chain Monte Carlo sampler for posterior inference. We evaluate the performance of the prior and the robustness of the resulting inference in a simulation study, providing a comparison with popular Dirichlet process mixtures and hidden Markov models. Finally, we develop an application to the detection of chromosomal aberrations in breast cancer by leveraging array comparative genomic hybridization (CGH) data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1276457
title: A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates

description: We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure, this method produces clinically meaningful estimators in a variety of settings. It can be useful for practicing personalized medicine: determining from a large set of biomarkers, the subset of patients that can potentially benefit from a treatment. We apply the method to both simulated datasets and real trial data. The modified covariates idea can be used for other purposes, for example, large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1276459.v1
title: Generalized Species Sampling Priors With Latent Beta Reinforcements

description: Many popular Bayesian nonparametric priors can be characterized in terms of exchangeable species sampling sequences. However, in some applications, exchangeability may not be appropriate. We introduce a novel and probabilistically coherent family of nonexchangeable species sampling sequences characterized by a tractable predictive probability function with weights driven by a sequence of independent Beta random variables. We compare their theoretical clustering properties with those of the Dirichlet process and the two parameters Poisson–Dirichlet process. The proposed construction provides a complete characterization of the joint process, differently from existing work. We then propose the use of such process as prior distribution in a hierarchical Bayes’ modeling framework, and we describe a Markov chain Monte Carlo sampler for posterior inference. We evaluate the performance of the prior and the robustness of the resulting inference in a simulation study, providing a comparison with popular Dirichlet process mixtures and hidden Markov models. Finally, we develop an application to the detection of chromosomal aberrations in breast cancer by leveraging array comparative genomic hybridization (CGH) data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1276457.v1
title: A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates

description: We consider a setting in which we have a treatment and a potentially large number of covariates for a set of observations, and wish to model their relationship with an outcome of interest. We propose a simple method for modeling interactions between the treatment and covariates. The idea is to modify the covariate in a simple way, and then fit a standard model using the modified covariates and no main effects. We show that coupled with an efficiency augmentation procedure, this method produces clinically meaningful estimators in a variety of settings. It can be useful for practicing personalized medicine: determining from a large set of biomarkers, the subset of patients that can potentially benefit from a treatment. We apply the method to both simulated datasets and real trial data. The modified covariates idea can be used for other purposes, for example, large scale hypothesis testing for determining which of a set of covariates interact with a treatment variable. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1276396
title: ISQ Measurement Occasion 2 (with covariates and dep variables)

description: Data Manuscript:<br>Measuring the Quality of Individual Lectures: Development and Validation of the The Instructional Skills Questionnaire (ISQ) Datasets:<br>2015_d1t0covdepM.dat # Dataset 1 Measurement Occasion 0 , with covariates and dependent variables N=6009 complete cases<br>2015_d1t1covdepM.dat # Dataset 1 Measurement Occasion 1 , with covariates and dependent variables N=4766 complete cases<br>2015_d1t2covdepM.dat # Dataset 1 Measurement Occasion 2 , with covariates and dependent variables N=3821 complete cases variables: names are<br>Teacher Student2 #Teacher number, Student number<br>SCog SAff SReg # Student Learning Outcomes: Cognition, Affection, Regulation<br>C1 C2 # Dummy variables: Condition 1 and 2<br>Str1 Str2 Str3 Str4 # ISQ Dimension: Structure: items 1-4<br>Expl1 Expl2 Expl3 Expl4 # ISQ Dimension: Explication: items 1-4<br>Stim1 Stim2 Stim3 Stim4 # ISQ Dimension: Stimulation: items 1-4<br>Val1 Val2 Val3 Val4 # ISQ Dimension: Validation: items 1-4<br>Instr1 Instr2 Instr3 Instr4 # ISQ Dimension: Instruction: items 1-4<br>Comp1 Comp2 Comp3 Comp4 # ISQ Dimension: Comprehension: items 1-4<br>Act1 Act2 Act3 Act4 # ISQ Dimension: Activation: items 1-4
DOI: 10.6084/m9.figshare.1276397
title: Spss Amsterdam chess test

description: Data belonging to the Amsterdam chess tyest study
DOI: 10.6084/m9.figshare.1276399
title: The Amsterdam Chess Test: a psychometric analysis of chess expertise.

description: Journal paper
DOI: 10.6084/m9.figshare.1276395
title: ISQ Measurement Occasion 1 (with covariates and dep variables)

description: Data Manuscript:Measuring the Quality of Individual Lectures: Development and Validation of the The Instructional Skills Questionnaire (ISQ) Datasets:<br>2015_d1t0covdepM.dat # Dataset 1 Measurement Occasion 0 , with covariates and dependent variables N=6009 complete cases<br>2015_d1t1covdepM.dat # Dataset 1 Measurement Occasion 1 , with covariates and dependent variables N=4766 complete cases<br>2015_d1t2covdepM.dat # Dataset 1 Measurement Occasion 2 , with covariates and dependent variables N=3821 complete casesvariables: names are<br>Teacher Student2 #Teacher number, Student number<br>SCog SAff SReg # Student Learning Outcomes: Cognition, Affection, Regulation<br>C1 C2 # Dummy variables: Condition 1 and 2<br>Str1 Str2 Str3 Str4 # ISQ Dimension: Structure: items 1-4<br>Expl1 Expl2 Expl3 Expl4 # ISQ Dimension: Explication: items 1-4<br>Stim1 Stim2 Stim3 Stim4 # ISQ Dimension: Stimulation: items 1-4<br>Val1 Val2 Val3 Val4 # ISQ Dimension: Validation: items 1-4<br>Instr1 Instr2 Instr3 Instr4 # ISQ Dimension: Instruction: items 1-4<br>Comp1 Comp2 Comp3 Comp4 # ISQ Dimension: Comprehension: items 1-4<br>Act1 Act2 Act3 Act4 # ISQ Dimension: Activation: items 1-4
DOI: 10.6084/m9.figshare.1276397.v1
title: Spss Amsterdam chess test

description: Data belonging to the Amsterdam chess tyest study