cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26840212.v1
title: Genome-wide association analysis reveals genetic architecture of growth and inner shell color traits in freshwater pearl mussel Hyriopsis cumingii (Lea 1852)

description: Triangle sail mussel (Hyriopsis cumingii, Lea 1852) is the most important freshwater pearl mussel in China. Growth traits of host mussels and inner shell color traits of donor mussels are critical determinants for pearl size and color. In this study, we performed GWAS analysis to explore the genetic architecture of growth and inner shell color traits.
DOI: 10.5281/zenodo.12779134
title: Ketterer et al. "The putative Type 4 secretion system effector BspD is involved in maintaining envelope integrity of the pathogen Brucella"

description: Supplementary Data to Ketterer et al. "The putative Type 4 secretion system effector BspD is involved in maintaining envelope integrity of the pathogen Brucella"
DOI: 10.5281/zenodo.12779135
title: Ketterer et al. "The putative Type 4 secretion system effector BspD is involved in maintaining envelope integrity of the pathogen Brucella"

description: Supplementary Data to Ketterer et al. "The putative Type 4 secretion system effector BspD is involved in maintaining envelope integrity of the pathogen Brucella"
DOI: 10.15468/dl.pw96xu
title: Occurrence Download

description: A dataset containing 494 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Gabrius osseticus (Kolenati, 1846)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 494 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102479-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4r8d8x
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Neriene carinata Blackwall, 1864",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102480-240626123714530/datasets/export for details.
DOI: 10.15468/dl.ycmpf4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Lithobius schubarti Demange, 1959",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102481-240626123714530/datasets/export for details.
DOI: 10.15468/dl.f3s5dp
title: Occurrence Download

description: A dataset containing 101 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Gabrius austriacus Scheerpeltz, 1947",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 101 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102482-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.25265083
title: 7head test

description: This is a test for figshare
DOI: 10.6084/m9.figshare.25265083.v2
title: 7head test

description: This is a test for figshare
DOI: 10.6084/m9.figshare.25265083.v1
title: test

description: This is a test for figshare
DOI: 10.15468/dl.89s9dq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Lithobius creticus Dobroruka, 1977",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102484-240626123714530/datasets/export for details.
DOI: 10.15468/dl.k8pzc3
title: Occurrence Download

description: A dataset containing 5585 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Neriene clathrata (Sundevall, 1830)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 5585 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102483-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.32mmvt
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Gabrius badius (Kiesenwetter, 1858)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102485-240626123714530/datasets/export for details.
DOI: 10.15468/dl.6wzkq8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Lithobius stammeri Verhoeff, 1939",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102486-240626123714530/datasets/export for details.
DOI: 10.15468/dl.937dk6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Neriene furva Blackwall, 1836",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102487-240626123714530/datasets/export for details.
DOI: 10.15468/dl.vdc6x8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Gabrius heres Smetana, 1962",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102489-240626123714530/datasets/export for details.
DOI: 10.15468/dl.5xztjz
title: Occurrence Download

description: A dataset containing 13303 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coreopsis lanceolata L."
 ]
}

 The dataset includes 13303 records from 453 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102488-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tuvxze
title: Occurrence Download

description: A dataset containing 38944509 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (September, October, November)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 2001-2010"
 ]
}

 The dataset includes 38944509 records from 851 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0102470-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.11662314
title: Pan-cancer analysis of RNA methyltransferases identifies FTSJ3 as a potential regulator of breast cancer progression

description: RNA methylation, catalysed by a set of RNA methyltransferases (RNMTs), modulates RNA structures, properties, and biological functions. RNMTs are increasingly documented to be dysregulated in various human diseases, particularly developmental disorders and cancer. However, the genomic and transcriptomic alterations of RNMTs, as well as their functional roles in human cancer, are limited. In this study, we utilized an unbiased approach to examine copy number alterations and mutation rates of 58 RNMTs in more than 10,000 clinical samples across 32 human cancer types. We also investigated these alterations and RNMT expression level as they related to clinical features such as tumour subtype, grade, and survival in a large cohort of tumour samples, focusing on breast cancer. Loss-of-function analysis was performed to examine RNMT candidates with important roles in growth and viability of breast cancer cells. We identified a subset of RNMTs, notably <i>TRMT12, NSUN2, TARBP1</i>, and <i>FTSJ3</i>, that were amplified or mutated in a subset of human cancers. Several RNMTs were significantly associated with breast cancer aggressiveness and poor prognosis. Loss-of-function analysis indicated FTSJ3, a 2ʹ-O-Me methyltransferase, as a candidate RNMT with functional roles in promoting cancer growth and survival. A subset of RNMTs, like FTSJ3, represents promising novel targets for anticancer drug discovery. Our findings provide a framework for further study of the functional consequences of RNMT alterations in human cancer and for developing therapies that target cancer-promoting RNMTs in the future.
DOI: 10.6084/m9.figshare.12186255
title: Additional file 2 of Changes of the glutathione redox system during the weaning transition in piglets, in relation to small intestinal morphology and barrier function

description: Additional file 2 Table S2 Overall effects of birht weight (BW), weaning treatment (WT) and days post-weaning (DPW) (n = 36-90). Table S3 The interaction effect of birht weight (BiW) and days post-weaning (DPW) (n = 18). Table S4 The interaction effect of weaning treatment (WT) and days post-weaning (DPW) (n = 12). Table S5 The interaction effect of birht weight (BiW) and weaning treatment (WT) (n = 30).
DOI: 10.6084/m9.figshare.11662314.v1
title: Pan-cancer analysis of RNA methyltransferases identifies FTSJ3 as a potential regulator of breast cancer progression

description: RNA methylation, catalysed by a set of RNA methyltransferases (RNMTs), modulates RNA structures, properties, and biological functions. RNMTs are increasingly documented to be dysregulated in various human diseases, particularly developmental disorders and cancer. However, the genomic and transcriptomic alterations of RNMTs, as well as their functional roles in human cancer, are limited. In this study, we utilized an unbiased approach to examine copy number alterations and mutation rates of 58 RNMTs in more than 10,000 clinical samples across 32 human cancer types. We also investigated these alterations and RNMT expression level as they related to clinical features such as tumour subtype, grade, and survival in a large cohort of tumour samples, focusing on breast cancer. Loss-of-function analysis was performed to examine RNMT candidates with important roles in growth and viability of breast cancer cells. We identified a subset of RNMTs, notably <i>TRMT12, NSUN2, TARBP1</i>, and <i>FTSJ3</i>, that were amplified or mutated in a subset of human cancers. Several RNMTs were significantly associated with breast cancer aggressiveness and poor prognosis. Loss-of-function analysis indicated FTSJ3, a 2ʹ-O-Me methyltransferase, as a candidate RNMT with functional roles in promoting cancer growth and survival. A subset of RNMTs, like FTSJ3, represents promising novel targets for anticancer drug discovery. Our findings provide a framework for further study of the functional consequences of RNMT alterations in human cancer and for developing therapies that target cancer-promoting RNMTs in the future.
DOI: 10.25440/smu.17429465
title: Selamat: Binary and experiment data

description: This is a tool developed based on the paper "Automated synthesis of local time requirement for service composition" published in <i>Software and Systems Modeling</i> in 2020.
DOI: 10.25440/smu.17429465.v1
title: Selamat: Binary and experiment data

description: This is a tool developed based on the paper "Automated synthesis of local time requirement for service composition" published in <i>Software and Systems Modeling</i> in 2020.
DOI: 10.6084/m9.figshare.23196672
title: On Simulating Skewed and Cluster-Weighted Data for Studying Performance of Clustering Algorithms

description: In this article, extensions to the recently introduced concept of pairwise overlap between mixture components are proposed. The notion of overlap is useful for studying the systematic performance of clustering algorithms. Existing methods can be used for simulating elliptical data according to pre-specified overlap characteristics. First, an approach to simulating skewed clusters with a desired overlap is proposed. Next, an extension to measuring overlap in cluster-weighted models is considered. Thus, this article provides important extensions to the existing methods for simulating heterogeneous data for studying the systematic performance of clustering algorithms. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.23196672.v1
title: On simulating skewed and cluster-weighted data for studying performance of clustering algorithms

description: In this paper, extensions to the recently introduced concept of pairwise overlap between mixture components are proposed. The notion of overlap is useful for studying the systematic performance of clustering algorithms. Existing methods can be used for simulating elliptical data according to pre-specified overlap characteristics. First, an approach to simulating skewed clusters with a desired overlap is proposed. Next, an extension to measuring overlap in cluster-weighted models is considered. Thus, this paper provides important extensions to the exisiting methods for simulating heterogeneous data for studying the systematic performance of clustering algorithms.
DOI: 10.6084/m9.figshare.12186306
title: Additional file 1 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 1.
DOI: 10.6084/m9.figshare.12186333.v1
title: Additional file 6 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 6.
DOI: 10.6084/m9.figshare.12186321.v1
title: Additional file 4 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 4.
DOI: 10.6084/m9.figshare.12186309.v1
title: Additional file 2 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 2.
DOI: 10.6084/m9.figshare.12186309
title: Additional file 2 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 2.
DOI: 10.6084/m9.figshare.12186315
title: Additional file 3 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 3.
DOI: 10.6084/m9.figshare.12186306.v1
title: Additional file 1 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 1.
DOI: 10.6084/m9.figshare.12186315.v1
title: Additional file 3 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 3.
DOI: 10.6084/m9.figshare.12186321
title: Additional file 4 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 4.
DOI: 10.6084/m9.figshare.12186339
title: Additional file 7 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 7.
DOI: 10.6084/m9.figshare.17429657
title: Supplementary data set for “A Nanoscale Shape-Discovery Framework Supporting Systematic Investigations of Shape-Dependent Biological Effects and Immunomodulation”—a submission to ACS Nano

description: Dataset associated with the paper "A Nanoscale
Shape-Discovery Framework Supporting Systematic Investigations of
Shape-Dependent Biological Effects and Immunomodulation"<br>
DOI: 10.6084/m9.figshare.12186327.v1
title: Additional file 5 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 5.
DOI: 10.6084/m9.figshare.12186333
title: Additional file 6 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 6.
DOI: 10.6084/m9.figshare.12186339.v1
title: Additional file 7 of Machine learning-selected variables associated with CD4 T cell recovery under antiretroviral therapy in very advanced HIV infection

description: Additional file 7.
DOI: 10.6084/m9.figshare.24245665
title: Discovery and inference of a causal network with hidden confounding*

description: This article proposes a novel causal discovery and inference method called GrIVET for a Gaussian directed acyclic graph with unmeasured confounders. GrIVET consists of an order-based causal discovery method and a likelihood-based inferential procedure. For causal discovery, we generalize the existing peeling algorithm to estimate the ancestral relations and candidate instruments in the presence of hidden confounders. Based on this, we propose a new procedure for instrumental variable estimation of each direct effect by separating it from any mediation effects. For inference, we develop a new likelihood ratio test of multiple causal effects that is able to account for the unmeasured confounders. Theoretically, we prove that the proposed method has desirable guarantees, including robustness to invalid instruments and uncertain interventions, estimation consistency, low-order polynomial time complexity, and validity of asymptotic inference. Numerically, GrIVET performs well and compares favorably against state-of-the-art competitors. Furthermore, we demonstrate the utility and effectiveness of the proposed method through an application inferring regulatory pathways from Alzheimer’s disease gene expression data.
DOI: 10.6084/m9.figshare.8987189
title: Effects of Cold Rolling Deformation on Microstructure and Damping Capacity of a Fe-Mn-Cr-Co-Si Alloy

description: The microstructure evolution of Fe-19Mn-8Cr-1Co-0.2Si (wt.%) alloy and Fe-19Mn (wt.%) alloy during cold rolling and its effect on the damping capacity of the two alloys were investigated. It was shown that the damping capacity of the two alloys was enhanced significantly owing to the deformation-induced ε-martensite and stacking faults. The Fe-19Mn-8Cr-1Co-0.2Si alloy exhibited an accelerated phase transformation from γ-austenite to ε-martensite due to a higher content of retained γ-austenite and larger grain sizes compared with the Fe-19Mn alloy, resulting in a higher maximal increment of damping capacity in this alloy caused by deformation. It was observed that no twinned ε-martensite was generated in the Fe-19Mn-8Cr-1Co-0.2Si alloy during cold rolling, resulting in a remarkable increase in the volume fraction of α'-martensite owing to no impediment to ε → α' transformation, hence the deterioration of damping capacity was slow because the α'-martensite weakened the pinning effect of dislocations on damping sources. In addition, new damping sources were provided due to the occurance of γ-austenite twinning in the Fe-19Mn-8Cr-1Co-0.2Si alloy.
DOI: 10.6084/m9.figshare.8987189.v1
title: Effects of Cold Rolling Deformation on Microstructure and Damping Capacity of a Fe-Mn-Cr-Co-Si Alloy

description: The microstructure evolution of Fe-19Mn-8Cr-1Co-0.2Si (wt.%) alloy and Fe-19Mn (wt.%) alloy during cold rolling and its effect on the damping capacity of the two alloys were investigated. It was shown that the damping capacity of the two alloys was enhanced significantly owing to the deformation-induced ε-martensite and stacking faults. The Fe-19Mn-8Cr-1Co-0.2Si alloy exhibited an accelerated phase transformation from γ-austenite to ε-martensite due to a higher content of retained γ-austenite and larger grain sizes compared with the Fe-19Mn alloy, resulting in a higher maximal increment of damping capacity in this alloy caused by deformation. It was observed that no twinned ε-martensite was generated in the Fe-19Mn-8Cr-1Co-0.2Si alloy during cold rolling, resulting in a remarkable increase in the volume fraction of α'-martensite owing to no impediment to ε → α' transformation, hence the deterioration of damping capacity was slow because the α'-martensite weakened the pinning effect of dislocations on damping sources. In addition, new damping sources were provided due to the occurance of γ-austenite twinning in the Fe-19Mn-8Cr-1Co-0.2Si alloy.