cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1473746
title: Objective Bayesian Survival Analysis Using Shape Mixtures of Log-Normal Distributions

description: Survival models such as the Weibull or log-normal lead to inference that is not robust to the presence of outliers. They also assume that all heterogeneity between individuals can be modeled through covariates. This article considers the use of infinite mixtures of lifetime distributions as a solution for these two issues. This can be interpreted as the introduction of a random effect in the survival distribution. We introduce the family of shape mixtures of log-normal distributions, which covers a wide range of density and hazard functions. Bayesian inference under nonsubjective priors based on the Jeffreys’ rule is examined and conditions for posterior propriety are established. The existence of the posterior distribution on the basis of a sample of point observations is not always guaranteed and a solution through set observations is implemented. In addition, we propose a method for outlier detection based on the mixture structure. A simulation study illustrates the performance of our methods under different scenarios and an application to a real dataset is provided. Supplementary materials for the article, which include R code, are available online.
DOI: 10.6084/m9.figshare.1473748.v1
title: Index Models for Sparsely Sampled Functional Data

description: The regression problem involving functional predictors has many important applications and a number of functional regression methods have been developed. However, a common complication in functional data analysis is one of sparsely observed curves, that is predictors that are observed, with error, on a small subset of the possible time points. Such sparsely observed data induce an <i>errors-in-variables</i> model, where one must account for measurement error in the functional predictors. Faced with sparsely observed data, most current functional regression methods simply estimate the unobserved predictors and treat them as fully observed; thus failing to account for the extra uncertainty from the measurement error. We propose a new functional errors-in-variables approach, sparse index model functional estimation (SIMFE), which uses a functional index model formulation to deal with sparsely observed predictors. SIMFE has several advantages over more traditional methods. First, the index model implements a nonlinear regression and uses an accurate supervised method to estimate the lower dimensional space into which the predictors should be projected. Second, SIMFE can be applied to both scalar and functional responses and multiple predictors. Finally, SIMFE uses a mixed effects model to effectively deal with very sparsely observed functional predictors and to correctly model the measurement error. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1473745
title: Craniodental and postcranial morphology of <i>Indohyaenodon raoi</i> from the early eocene of india, and its implications for ecology, phylogeny, and biogeography of hyaenodontid mammals

description: ABSTRACTNew remains of the early Eocene hyaenodontid <i>Indohyaenodon raoi</i> are described from the Vastan Lignite Mine in Gujarat, western India, including the first known rostrum, upper dentition, and postcrania, substantially expanding our knowledge of the species and providing insights into its functional morphology and relationships. Craniodental morphology suggests that <i>I. raoi</i> had a broad diet, including non-vertebrate material as well as flesh of a diversity of prey species. Postcranial morphology is broadly similar to that of other early hyaenodontids and suggests a scansorial locomotor repertoire. Dental morphology indicates that <i>I. raoi</i> is closely related to other South Asian hyaenodontids, with shared features including strong cingula, narrow premolars, and a reduced P4 protocone. We present the most comprehensive phylogenetic analysis of Hyaenodontidae to date, which corroborates this relationship but finds South Asian hyaenodontids to be the stem of a group that includes most African hyaenodontids. This and other higher-level relationships within Hyaenodontidae are, however, weakly supported, and substantially different alternative hypotheses of relationships are not significantly less parsimonious, reflecting strong character conflict. Factors contributing to this conflict include the isolation of hyaenodontid faunas on different continents during much of the Eocene, canalization and simplification of carnivorous dentitions, and a lack of non-dental material for critical hyaenodontid groups. The new phylogeny is consistent with either an African or an Asian origin for the group.SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at http://www.tandfonline.com/UJVP
DOI: 10.6084/m9.figshare.1473748.v3
title: Index Models for Sparsely Sampled Functional Data

description: The regression problem involving functional predictors has many important applications and a number of functional regression methods have been developed. However, a common complication in functional data analysis is one of sparsely observed curves, that is predictors that are observed, with error, on a small subset of the possible time points. Such sparsely observed data induce an <i>errors-in-variables</i> model, where one must account for measurement error in the functional predictors. Faced with sparsely observed data, most current functional regression methods simply estimate the unobserved predictors and treat them as fully observed; thus failing to account for the extra uncertainty from the measurement error. We propose a new functional errors-in-variables approach, sparse index model functional estimation (SIMFE), which uses a functional index model formulation to deal with sparsely observed predictors. SIMFE has several advantages over more traditional methods. First, the index model implements a nonlinear regression and uses an accurate supervised method to estimate the lower dimensional space into which the predictors should be projected. Second, SIMFE can be applied to both scalar and functional responses and multiple predictors. Finally, SIMFE uses a mixed effects model to effectively deal with very sparsely observed functional predictors and to correctly model the measurement error. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1473748.v2
title: Index Models for Sparsely Sampled Functional Data

description: The regression problem involving functional predictors has many important applications and a number of functional regression methods have been developed. However, a common complication in functional data analysis is one of sparsely observed curves, that is predictors that are observed, with error, on a small subset of the possible time points. Such sparsely observed data induce an <i>errors-in-variables</i> model, where one must account for measurement error in the functional predictors. Faced with sparsely observed data, most current functional regression methods simply estimate the unobserved predictors and treat them as fully observed; thus failing to account for the extra uncertainty from the measurement error. We propose a new functional errors-in-variables approach, sparse index model functional estimation (SIMFE), which uses a functional index model formulation to deal with sparsely observed predictors. SIMFE has several advantages over more traditional methods. First, the index model implements a nonlinear regression and uses an accurate supervised method to estimate the lower dimensional space into which the predictors should be projected. Second, SIMFE can be applied to both scalar and functional responses and multiple predictors. Finally, SIMFE uses a mixed effects model to effectively deal with very sparsely observed functional predictors and to correctly model the measurement error. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.1473744
title: Functional analysis of phosphorylation of the mitotic centromere-associated kinesin by Aurora B kinase in human tumor cells

description: Mitotic centromere-associated kinesin (MCAK) is the best characterized member of the kinesin-13 family and plays important roles in microtubule dynamics during mitosis. Its activity and subcellular localization is tightly regulated by an orchestra of mitotic kinases, such as Aurora B. It is well known that serine 196 of MCAK is the major phosphorylation site of Aurora B in <i>Xenopus leavis</i> extracts and that this phosphorylation regulates its catalytic activity and subcellular localization. In the current study, we have addressed the conserved phosphorylation site serine 192 in human MCAK to characterize its function in more depth in human cancer cells. Our data confirm that S192 is the major phosphorylation site of Aurora B in human MCAK and that this phosphorylation has crucial roles in regulating its catalytic activity and localization at the kinetochore/centromere region in mitosis. Interfering with this phosphorylation leads to a delayed progression through prometa- and metaphase associated with mitotic defects in chromosome alignment and segregation. We show further that MCAK is involved in directional migration and invasion of tumor cells, and interestingly, interference with the S192 phosphorylation affects this capability of MCAK. These data provide the first molecular explanation for clinical observation, where an overexpression of MCAK was associated with lymphatic invasion and lymph node metastasis in gastric and colorectal cancer patients.
DOI: 10.6084/m9.figshare.1473744.v2
title: Functional analysis of phosphorylation of the mitotic centromere-associated kinesin by Aurora B kinase in human tumor cells

description: Mitotic centromere-associated kinesin (MCAK) is the best characterized member of the kinesin-13 family and plays important roles in microtubule dynamics during mitosis. Its activity and subcellular localization is tightly regulated by an orchestra of mitotic kinases, such as Aurora B. It is well known that serine 196 of MCAK is the major phosphorylation site of Aurora B in <i>Xenopus leavis</i> extracts and that this phosphorylation regulates its catalytic activity and subcellular localization. In the current study, we have addressed the conserved phosphorylation site serine 192 in human MCAK to characterize its function in more depth in human cancer cells. Our data confirm that S192 is the major phosphorylation site of Aurora B in human MCAK and that this phosphorylation has crucial roles in regulating its catalytic activity and localization at the kinetochore/centromere region in mitosis. Interfering with this phosphorylation leads to a delayed progression through prometa- and metaphase associated with mitotic defects in chromosome alignment and segregation. We show further that MCAK is involved in directional migration and invasion of tumor cells, and interestingly, interference with the S192 phosphorylation affects this capability of MCAK. These data provide the first molecular explanation for clinical observation, where an overexpression of MCAK was associated with lymphatic invasion and lymph node metastasis in gastric and colorectal cancer patients.
DOI: 10.6084/m9.figshare.1473746.v1
title: Objective Bayesian Survival Analysis Using Shape Mixtures of Log-Normal Distributions

description: Survival models such as the Weibull or log-normal lead to inference that is not robust to the presence of outliers. They also assume that all heterogeneity between individuals can be modeled through covariates. This article considers the use of infinite mixtures of lifetime distributions as a solution for these two issues. This can be interpreted as the introduction of a random effect in the survival distribution. We introduce the family of shape mixtures of log-normal distributions, which covers a wide range of density and hazard functions. Bayesian inference under nonsubjective priors based on the Jeffreys’ rule is examined and conditions for posterior propriety are established. The existence of the posterior distribution on the basis of a sample of point observations is not always guaranteed and a solution through set observations is implemented. In addition, we propose a method for outlier detection based on the mixture structure. A simulation study illustrates the performance of our methods under different scenarios and an application to a real dataset is provided. Supplementary materials for the article, which include R code, are available online.
DOI: 10.6084/m9.figshare.1473744.v1
title: Functional analysis of phosphorylation of the mitotic centromere-associated kinesin by Aurora B kinase in human tumor cells

description: Mitotic centromere-associated kinesin (MCAK) is the best characterized member of the kinesin-13 family and plays important roles in microtubule dynamics during mitosis. Its activity and subcellular localization is tightly regulated by an orchestra of mitotic kinases, such as Aurora B. It is well known that serine 196 of MCAK is the major phosphorylation site of Aurora B in <i>Xenopus leavis</i> extracts and that this phosphorylation regulates its catalytic activity and subcellular localization. In the current study, we have addressed the conserved phosphorylation site serine 192 in human MCAK to characterize its function in more depth in human cancer cells. Our data confirm that S192 is the major phosphorylation site of Aurora B in human MCAK and that this phosphorylation has crucial roles in regulating its catalytic activity and localization at the kinetochore/centromere region in mitosis. Interfering with this phosphorylation leads to a delayed progression through prometa- and metaphase associated with mitotic defects in chromosome alignment and segregation. We show further that MCAK is involved in directional migration and invasion of tumor cells, and interestingly, interference with the S192 phosphorylation affects this capability of MCAK. These data provide the first molecular explanation for clinical observation, where an overexpression of MCAK was associated with lymphatic invasion and lymph node metastasis in gastric and colorectal cancer patients.
DOI: 10.6084/m9.figshare.1473746.v3
title: Objective Bayesian Survival Analysis Using Shape Mixtures of Log-Normal Distributions

description: Survival models such as the Weibull or log-normal lead to inference that is not robust to the presence of outliers. They also assume that all heterogeneity between individuals can be modeled through covariates. This article considers the use of infinite mixtures of lifetime distributions as a solution for these two issues. This can be interpreted as the introduction of a random effect in the survival distribution. We introduce the family of shape mixtures of log-normal distributions, which covers a wide range of density and hazard functions. Bayesian inference under nonsubjective priors based on the Jeffreys’ rule is examined and conditions for posterior propriety are established. The existence of the posterior distribution on the basis of a sample of point observations is not always guaranteed and a solution through set observations is implemented. In addition, we propose a method for outlier detection based on the mixture structure. A simulation study illustrates the performance of our methods under different scenarios and an application to a real dataset is provided. Supplementary materials for the article, which include R code, are available online.
DOI: 10.6084/m9.figshare.1473745.v1
title: Craniodental and postcranial morphology of <i>Indohyaenodon raoi</i> from the early Eocene of India, and its implications for ecology, phylogeny, and biogeography of hyaenodontid mammals

description: ABSTRACTNew remains of the early Eocene hyaenodontid <i>Indohyaenodon raoi</i> are described from the Vastan Lignite Mine in Gujarat, western India, including the first known rostrum, upper dentition, and postcrania, substantially expanding our knowledge of the species and providing insights into its functional morphology and relationships. Craniodental morphology suggests that <i>I. raoi</i> had a broad diet, including non-vertebrate material as well as flesh of a diversity of prey species. Postcranial morphology is broadly similar to that of other early hyaenodontids and suggests a scansorial locomotor repertoire. Dental morphology indicates that <i>I. raoi</i> is closely related to other South Asian hyaenodontids, with shared features including strong cingula, narrow premolars, and a reduced P4 protocone. We present the most comprehensive phylogenetic analysis of Hyaenodontidae to date, which corroborates this relationship but finds South Asian hyaenodontids to be the stem of a group that includes most African hyaenodontids. This and other higher-level relationships within Hyaenodontidae are, however, weakly supported, and substantially different alternative hypotheses of relationships are not significantly less parsimonious, reflecting strong character conflict. Factors contributing to this conflict include the isolation of hyaenodontid faunas on different continents during much of the Eocene, canalization and simplification of carnivorous dentitions, and a lack of non-dental material for critical hyaenodontid groups. The new phylogeny is consistent with either an African or an Asian origin for the group.SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at http://www.tandfonline.com/UJVP
DOI: 10.6084/m9.figshare.1473746.v2
title: Objective Bayesian Survival Analysis Using Shape Mixtures of Log-Normal Distributions

description: Survival models such as the Weibull or log-normal lead to inference that is not robust to the presence of outliers. They also assume that all heterogeneity between individuals can be modeled through covariates. This article considers the use of infinite mixtures of lifetime distributions as a solution for these two issues. This can be interpreted as the introduction of a random effect in the survival distribution. We introduce the family of shape mixtures of log-normal distributions, which covers a wide range of density and hazard functions. Bayesian inference under nonsubjective priors based on the Jeffreys’ rule is examined and conditions for posterior propriety are established. The existence of the posterior distribution on the basis of a sample of point observations is not always guaranteed and a solution through set observations is implemented. In addition, we propose a method for outlier detection based on the mixture structure. A simulation study illustrates the performance of our methods under different scenarios and an application to a real dataset is provided. Supplementary materials for the article, which include R code, are available online.
DOI: 10.6084/m9.figshare.1473745.v3
title: Craniodental and postcranial morphology of <i>Indohyaenodon raoi</i> from the early eocene of india, and its implications for ecology, phylogeny, and biogeography of hyaenodontid mammals

description: ABSTRACTNew remains of the early Eocene hyaenodontid <i>Indohyaenodon raoi</i> are described from the Vastan Lignite Mine in Gujarat, western India, including the first known rostrum, upper dentition, and postcrania, substantially expanding our knowledge of the species and providing insights into its functional morphology and relationships. Craniodental morphology suggests that <i>I. raoi</i> had a broad diet, including non-vertebrate material as well as flesh of a diversity of prey species. Postcranial morphology is broadly similar to that of other early hyaenodontids and suggests a scansorial locomotor repertoire. Dental morphology indicates that <i>I. raoi</i> is closely related to other South Asian hyaenodontids, with shared features including strong cingula, narrow premolars, and a reduced P4 protocone. We present the most comprehensive phylogenetic analysis of Hyaenodontidae to date, which corroborates this relationship but finds South Asian hyaenodontids to be the stem of a group that includes most African hyaenodontids. This and other higher-level relationships within Hyaenodontidae are, however, weakly supported, and substantially different alternative hypotheses of relationships are not significantly less parsimonious, reflecting strong character conflict. Factors contributing to this conflict include the isolation of hyaenodontid faunas on different continents during much of the Eocene, canalization and simplification of carnivorous dentitions, and a lack of non-dental material for critical hyaenodontid groups. The new phylogeny is consistent with either an African or an Asian origin for the group.SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at http://www.tandfonline.com/UJVP
DOI: 10.6084/m9.figshare.1473745.v2
title: Craniodental and postcranial morphology of <i>Indohyaenodon raoi</i> from the early eocene of india, and its implications for ecology, phylogeny, and biogeography of hyaenodontid mammals

description: ABSTRACTNew remains of the early Eocene hyaenodontid <i>Indohyaenodon raoi</i> are described from the Vastan Lignite Mine in Gujarat, western India, including the first known rostrum, upper dentition, and postcrania, substantially expanding our knowledge of the species and providing insights into its functional morphology and relationships. Craniodental morphology suggests that <i>I. raoi</i> had a broad diet, including non-vertebrate material as well as flesh of a diversity of prey species. Postcranial morphology is broadly similar to that of other early hyaenodontids and suggests a scansorial locomotor repertoire. Dental morphology indicates that <i>I. raoi</i> is closely related to other South Asian hyaenodontids, with shared features including strong cingula, narrow premolars, and a reduced P4 protocone. We present the most comprehensive phylogenetic analysis of Hyaenodontidae to date, which corroborates this relationship but finds South Asian hyaenodontids to be the stem of a group that includes most African hyaenodontids. This and other higher-level relationships within Hyaenodontidae are, however, weakly supported, and substantially different alternative hypotheses of relationships are not significantly less parsimonious, reflecting strong character conflict. Factors contributing to this conflict include the isolation of hyaenodontid faunas on different continents during much of the Eocene, canalization and simplification of carnivorous dentitions, and a lack of non-dental material for critical hyaenodontid groups. The new phylogeny is consistent with either an African or an Asian origin for the group.SUPPLEMENTAL DATA—Supplemental materials are available for this article for free at http://www.tandfonline.com/UJVP