cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12992188
title: Additional file 5 of Theoretical characterisation of strand cross-correlation in ChIP-seq

description: Additional file 5 ChIP-seq analysis results of the strand cross-correlation based metrics and peak calling.
DOI: 10.21227/mct4-4d44
title: RECOVERY-FA19: Ultra-Widefield Fluorescein Angiography Vessel Detection Dataset

description: RECOVERY-FA19 dataset is established for development and evaluation of retinal vessel detection algorithms in fluorescein angiography (FA). RECOVERY-FA19 provides 8 high-resolution ultra-widefield FA images acquired using Optos California P200DTx camera and corresponding labeled binary vessel maps.
DOI: 10.6084/m9.figshare.12991172.v1
title: R0229_20181024a_videos

description: Rat 0229, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.12991673.v1
title: Additional file 1 of Non-invasive measurement of choroid plexus apparent blood flow with arterial spin labeling

description: Additional file 1: Figures. Spatial distributions of the choroid plexus ASL measures overlaid on the T1 weighted images of the other volunteers. (a) apparent blood flow (ml/100g/min), (b) arterial transit time (s) and (c) longitudinal relaxation time T1 (s).
DOI: 10.6084/m9.figshare.12991747.v1
title: Additional file 2 of Validity of the dispersion relations in magnetotellurics. Part II: synthetic and field data

description: Additional file 2. Field data pack.
DOI: 10.6084/m9.figshare.12991763.v1
title: Additional file 3 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 3. Gene expression for TRP channels. Blue color indicates TRP channels expressed in all SCTs or all MCTs. Red color indicates TRP channels with no transcripts in all SCTs (top) or all SCT and MCTs (bottom).
DOI: 10.6084/m9.figshare.12991766.v1
title: Additional file 4 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 4. Gene expression for ENaCs. Red color indicates ENaCs with no transcripts in all SCTs or all MCTs.
DOI: 10.6084/m9.figshare.12991769.v1
title: Additional file 5 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 5. Gene expression for NMDA receptors. Blue color indicates NMDArs expressed in all SCTs or all MCTs. Red color indicates NMDArs with no transcripts in all SCTs or all MCTs.
DOI: 10.6084/m9.figshare.12991772.v1
title: Additional file 6 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 6. Gene expression for class A GPCRs. Yellow color indicates GPCR expression &gt; 50 TPM. Blue color indicates tuning GPCRs expressed in all SCTs or all MCTs. Red color indicates GPCRs with no transcripts in all SCTs or all MCTs.
DOI: 10.6084/m9.figshare.12991775.v1
title: Additional file 7 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 7. Gene expression for G proteins and other molecules in signaling cascades. Blue color indicates tuning sequences expressed in all SCTs or all MCTs. Red color indicates sequences with no transcripts in all SCTs or all MCTs.
DOI: 10.6084/m9.figshare.12991778.v1
title: Additional file 8 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 8. DESeq2 comparison for LF vs. brain.
DOI: 10.6084/m9.figshare.12991781.v1
title: Additional file 9 of Single cell transcriptomes reveal expression patterns of chemoreceptor genes in olfactory sensory neurons of the Caribbean spiny lobster, Panulirus argus

description: Additional file 9. DESeq2 comparison for LF vs. leg dactyl.
DOI: 10.6084/m9.figshare.12991792.v1
title: Additional file 3 of Altered respiratory microbiota composition and functionality associated with asthma early in life

description: Additional file 3: Table S1. Summary of Bacterial and Fungal diversity and Prevalence Among Healthy and Asthmatic Groups Using Kruskal-Wallace P-values and Benjamin-Hochberg Corrected Values.
DOI: 10.6084/m9.figshare.12991814.v1
title: Additional file 5 of The microbiota of the surface, dermis and subcutaneous tissue of dog skin

description: Additional file 5. Final ASV table (contaminants removed).
DOI: 10.6084/m9.figshare.12991853.v1
title: Additional file 2 of An open-access stress magnitude database for Germany and adjacent regions

description: Additional file 2. Stress magnitude database for Germany and adjacent regions as ASCII table.
DOI: 10.6084/m9.figshare.12991913.v1
title: Additional file 1 of Cannabis as entheogen: survey and interview data on the spiritual use of cannabis

description: Additional file 1. Supplemental online material: Survey questionnaire as PDF, SPSS dataset, and online appendix.
DOI: 10.6084/m9.figshare.12991948.v1
title: Additional file 1 of Maternal and newborn health priority setting partnership in rural Uganda in association with the James Lind Alliance: a study protocol

description: Additional file 1. Characteristics of governance team and participants.
DOI: 10.6084/m9.figshare.12992675
title: Western Blot Uncropped Results

description: This is a meaningful Information for researchers. <br>
DOI: 10.6084/m9.figshare.12992675.v1
title: Western Blot Uncropped Results

description: This is a meaningful Information for researchers. <br>
DOI: 10.6084/m9.figshare.12992075.v1
title: Additional file 2 of Dutch DALYs, current and future burden of disease in the Netherlands

description: Additional file 2.
DOI: 10.6084/m9.figshare.12992078.v1
title: Additional file 1 of Sequence variations of ACVRL1 play a critical role in hepatic vascular malformations in hereditary hemorrhagic telangiectasia

description: Additional file 1.
DOI: 10.6084/m9.figshare.12992116.v1
title: Additional file 3 of Habitat disturbance influences the skin microbiome of a rediscovered neotropical-montane frog

description: Additional file 3 : Table S5. Fold-changes of bacterial ASVs detected on the skin of tadpoles that differ between undisturbed/disturbed habitats. Table S6. Fold-changes of bacterial ASVs detected on the skin of adults that differ between undisturbed/disturbed habitats.
DOI: 10.6084/m9.figshare.12992177.v1
title: Additional file 2 of Recovery and resiliency of skin microbial communities on the southern leopard frog (Lithobates sphenocephalus) following two biotic disturbances

description: Additional file 2: Table S2. Results of LefSe biomarker identification for each timepoint (T1-T6) as reflected in Fig. 1. Presented are significant biomarker OTUs, with LogMaxMean values, Class (treatment OTUs are biomarkers of), LDA and associated p-values.
DOI: 10.6084/m9.figshare.12992179.v1
title: Additional file 2 of Theoretical characterisation of strand cross-correlation in ChIP-seq

description: Additional file 2 The list of experiments in ENCODE and GRR project used in this study.
DOI: 10.6084/m9.figshare.12992182.v1
title: Additional file 3 of Theoretical characterisation of strand cross-correlation in ChIP-seq

description: Additional file 3 The R script to calculate the enriched region length from a peak model generated by MACS2. See Additional file 1 for details.
DOI: 10.6084/m9.figshare.12992183.v1
title: Additional file 3 of Recovery and resiliency of skin microbial communities on the southern leopard frog (Lithobates sphenocephalus) following two biotic disturbances

description: Additional file 3: Table S3. Primer sequences and MID (i5 and i7) sequences used for parsing sequences into experimental units.
DOI: 10.6084/m9.figshare.12992185.v1
title: Additional file 4 of Theoretical characterisation of strand cross-correlation in ChIP-seq

description: Additional file 4 The list of additionally analysed ChIP-seq experiments obtained from ENCODE and Roadmap project.
DOI: 10.6084/m9.figshare.12992186.v1
title: Additional file 4 of Recovery and resiliency of skin microbial communities on the southern leopard frog (Lithobates sphenocephalus) following two biotic disturbances

description: Additional file 4: Table S4. OTU taxonomic identification, representative sequence and full OTU by sample sequence count data are presented along with total number of sequences of each OTU.
DOI: 10.6084/m9.figshare.12992188.v1
title: Additional file 5 of Theoretical characterisation of strand cross-correlation in ChIP-seq

description: Additional file 5 ChIP-seq analysis results of the strand cross-correlation based metrics and peak calling.
DOI: 10.5517/ccdc.csd.cc25zjd3
title: CCDC 2025335: Experimental Crystal Structure Determination

description: Related Article: T.K. Shreekanth, H.S. Yathirajan, B. Kalluraya, S. Foro, C. Glidewell|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1605|doi:10.1107/S2056989020011676
DOI: 10.5517/ccdc.csd.cc25zjf4
title: CCDC 2025336: Experimental Crystal Structure Determination

description: Related Article: T.K. Shreekanth, H.S. Yathirajan, B. Kalluraya, S. Foro, C. Glidewell|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|1605|doi:10.1107/S2056989020011676
DOI: 10.15468/dwfn89
title: Biodiversity of the Api Nampa Conservation Area

description: This is a checklist of flora (angiosperms, gymnosperms, pteridophytes) and fauna (birds and insects) of Api Nampa Conservation Area. A total of 940 species are listed.
DOI: 10.5281/zenodo.4045172
title: Data from: Genetic admixture increases phenotypic diversity in the nectar yeast Metschnikowia reukaufii,

description: Raw data and supplementary files for the manuscript "Genetic admixture increases phenotypic diversity in the nectar yeast <em>Metschnikowia reukaufii</em>." ------------------- <strong>Table S5.xlsx </strong>-- Pairwise correlations between phenotypic traits of <em>Metschnikowia reukaufii</em>. <strong>Table S6.xlsx</strong> -- Detailed results obtained in tests of phylogenetic signal for different phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>. <strong>Table S7.xlsx</strong> -- Detailed model fitting results obtained for phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>. <strong>mronlyvcf-renamed.vcf</strong> -- High coverage SNPs obtained from whole genome mapping of 73 <em>Metschnikowia reukaufii</em> strains to diploid reference (mean coverage = 47.9×, range 23 – 116×). <strong>MR_phenotypes.xlsx</strong> -- Phenotypic data obtained for 73 <em>Metschnikowia reukaufii</em> strains.
DOI: 10.5281/zenodo.3677192
title: Data from: Genetic admixture increases phenotypic diversity in the nectar yeast Metschnikowia reukaufii,

description: Raw data and supplementary files for the manuscript "Genetic admixture increases phenotypic diversity in the nectar yeast <em>Metschnikowia reukaufii</em>." ------------------- <strong>Table S5.xlsx </strong>-- Pairwise correlations between phenotypic traits of <em>Metschnikowia reukaufii</em>. <strong>Table S6.xlsx</strong> -- Detailed results obtained in tests of phylogenetic signal for different phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>. <strong>Table S7.xlsx</strong> -- Detailed model fitting results obtained for phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>. <strong>mronlyvcf-renamed.vcf</strong> -- High coverage SNPs obtained from whole genome mapping of 73 <em>Metschnikowia reukaufii</em> strains to diploid reference (mean coverage = 47.9×, range 23 – 116×). <strong>MR_phenotypes.xlsx</strong> -- Phenotypic data obtained for 73 <em>Metschnikowia reukaufii</em> strains.
DOI: 10.6084/m9.figshare.12992912
title: Randomly generated dataset

description: This dataset is randomly generated using the built-in function from python random.randint(). This csv file contains 2 columns, index and value. Index represents the unique row id and value represents the randomly generated value at each row.
DOI: 10.6084/m9.figshare.12992912.v1
title: Randomly generated dataset

description: This dataset is randomly generated using the built-in function from python random.randint(). This csv file contains 2 columns, index and value. Index represents the unique row id and value represents the randomly generated value at each row.
DOI: 10.6084/m9.figshare.12992945.v1
title: Supplementary Table 1. Isolate ID, accession number, species, sequence type (ST), and date of collection (DOC).

description: Supplementary Table 1 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992945
title: Supplementary Table 1. Isolate ID, accession number, species, sequence type (ST), and date of collection (DOC).

description: Supplementary Table 1 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992927
title: Supplementary Material for: Die Prognose psychotherapeutischer Behandlungsergebnisse im naturalistischen Setting durch Belastungsindikatoren zu Behandlungsbeginn

description: <b><i>Hintergrund:</i></b> Erfolgsprognosen ermöglichen eine stetige Weiterentwicklung und ökonomische Anwendung von Psychotherapie. Deren effizienter Einsatz in der Praxis bedarf einer einfach umzusetzenden Prognosestellung. Die vorliegende Studie prüft die Vorhersage von Therapieerfolg aufgrund des anfänglichen Belastungsniveaus. <b><i>Methoden:</i></b> Verwendet wurden Daten aus der Routineevaluation einer psychotherapeutischen Hochschulambulanz von 3’145 PatientInnen (M<sub>Alter</sub> = 35,8, 67% weiblich). Anhand vor Therapiebeginn vorliegender Kriterien (allgemeine psychische Be­lastung, Symptomatik, Vorbehandlung) wurden niedrig versus hoch belastete PatientInnen differenziert und bezüglich der Erfolgsmaße absolute Belastungsreduktion, (Early) Response, Remission und Therapieabbruch mithilfe von <i>t</i>-Tests und logistischen Regressionsanalysen verglichen. Response und Remission wurden über ein relatives (prozentuale Verbesserung) und ein absolutes Maß (Reliable Change Index, RCI) operationalisiert. <b><i>Ergebnisse:</i></b> Hohe psychische Bela­s­tung stand in negativem Zusammenhang mit Response gemäß prozentualer Verbesserung (OR = 0,62) und Remission (OR = 0,34) sowie in positivem Zusammenhang mit absoluter Belastungsreduktion (<i>d</i> = 0,63), RCI-Response (OR = 2,37) und Therapieabbruch (OR = 2,15). Early Response und Therapieabbruch nahmen im Zusammenhang von anfänglichem Belastungsniveau und Behandlungserfolg eine partiell vermittelnde Rolle ein. <b><i>Schlussfolgerungen:</i></b> Behandlungserfolge fallen bei hoher anfänglicher psychischer Belastung vergleichsweise geringer aus, wobei die Operationalisierung von Erfolg eine entscheidende Rolle spielt. Die vorgestellte Klassifizierung ist leicht umzusetzen und kann im Ausbildungssetting helfen, einer therapeutischen Überlastung entgegenzuwirken.
DOI: 10.6084/m9.figshare.12992963
title: Supplementary Material for: A Bayesian Hierarchical Framework for Pathway Analysis in Genome-Wide Association Studies

description: <b><i>Background:</i></b> Pathway analysis allows joint consideration of multiple SNPs belonging to multiple genes, which in turn belong to a biologically defined pathway. This type of analysis is usually more powerful than single-SNP analyses for detecting joint effects of variants in a pathway. <b><i>Methods:</i></b> We develop a Bayesian hierarchical model by fully modeling the 3-level hierarchy, namely, SNP-gene-pathway that is naturally inherent in the structure of the pathways, unlike the currently used ad hoc ways of combining such information. We model the effects at each level conditional on the effects of the levels preceding them within the generalized linear model framework. To deal with the high dimensionality, we regularize the regression coefficients through an appropriate choice of priors. The model is fit using a combination of iteratively weighted least squares and expectation-maximization algorithms to estimate the posterior modes and their standard errors. A normal approximation is used for inference. <b><i>Results:</i></b> We conduct simulations to study the proposed method and find that our method has higher power than some standard approaches in several settings for identifying pathways with multiple modest-sized variants. We illustrate the method by analyzing data from two genome-wide association studies on breast and renal cancers. <b><i>Conclusion:</i></b> Our method can be helpful in detecting pathway association.
DOI: 10.6084/m9.figshare.12992963.v1
title: Supplementary Material for: A Bayesian Hierarchical Framework for Pathway Analysis in Genome-Wide Association Studies

description: <b><i>Background:</i></b> Pathway analysis allows joint consideration of multiple SNPs belonging to multiple genes, which in turn belong to a biologically defined pathway. This type of analysis is usually more powerful than single-SNP analyses for detecting joint effects of variants in a pathway. <b><i>Methods:</i></b> We develop a Bayesian hierarchical model by fully modeling the 3-level hierarchy, namely, SNP-gene-pathway that is naturally inherent in the structure of the pathways, unlike the currently used ad hoc ways of combining such information. We model the effects at each level conditional on the effects of the levels preceding them within the generalized linear model framework. To deal with the high dimensionality, we regularize the regression coefficients through an appropriate choice of priors. The model is fit using a combination of iteratively weighted least squares and expectation-maximization algorithms to estimate the posterior modes and their standard errors. A normal approximation is used for inference. <b><i>Results:</i></b> We conduct simulations to study the proposed method and find that our method has higher power than some standard approaches in several settings for identifying pathways with multiple modest-sized variants. We illustrate the method by analyzing data from two genome-wide association studies on breast and renal cancers. <b><i>Conclusion:</i></b> Our method can be helpful in detecting pathway association.
DOI: 10.6084/m9.figshare.12992942
title: Supplementary Table 2. Details and results of different analysis levels and reference genome relatedness.

description: Supplementary Table 2 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992942.v1
title: Supplementary Table 2. Details and results of different analysis levels and reference genome relatedness.

description: Supplementary Table 2 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.5281/zenodo.4044664
title: Governor's Island Dataset for QGIS

description: <strong>Basic Global Dataset for GRASS GIS</strong><br> This archive contains a QGIS project and a geopackage with raster and vector data for Governor's Island, New York City, USA. The CRS is NAD83 / New York Long Island (ftUS) with the EPSG code 2263. <strong>Data Sources</strong> https://orthos.dhses.ny.gov/ https://data.cityofnewyork.us/ <strong>License</strong><br> This dataset is licensed under the ODC Public Domain Dedication and License 1.0 (PDDL) by Brendan Harmon.
DOI: 10.6084/m9.figshare.12992936
title: Supplementary Table 3. Details and results of different prophage and recombination region omission.

description: Supplementary Table 3 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992936.v1
title: Supplementary Table 3. Details and results of different prophage and recombination region omission.

description: Supplementary Table 3 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992948
title: Supplementary Table 4. Details and results of the cumulative approach to isolate inclusion.

description: Supplementary Table 4 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992948.v1
title: Supplementary Table 4. Details and results of the cumulative approach to isolate inclusion.

description: Supplementary Table 4 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992951
title: Supplementary Table 5. Details and results of the sliding window approach to isolate inclusion.

description: Supplementary Table 5 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992951.v1
title: Supplementary Table 5. Details and results of the sliding window approach to isolate inclusion.

description: Supplementary Table 5 for paper "Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria" by Gorrie et al.
DOI: 10.6084/m9.figshare.12992918
title: LDmatrices

description: output: This directory contains LD matrices that were used for generating the null distribution within LDna against which the 500 outlier SNP LD matrix was compared.<br>LDmat_500SNPs.txt: LD matrix for the 500 outlier Bayenv SNPs
DOI: 10.6084/m9.figshare.12992972
title: Linear Transformation

description: This dataset is a csv file resulted from a linear transformation y = 3*x+6 of 1000 randomly generated number between 0 - 100. It was generated by applying a linear transformation on 1000 data points generated from random.randint() function.
DOI: 10.6084/m9.figshare.12992972.v1
title: Linear Transformation

description: This dataset is a csv file resulted from a linear transformation y = 3*x+6 of 1000 randomly generated number between 0 - 100. It was generated by applying a linear transformation on 1000 data points generated from random.randint() function.
DOI: 10.5517/ccdc.csd.ccw0905
title: CCDC 804636: Experimental Crystal Structure Determination

description: Related Article: Claudia C. Gatto, Sebastião S. Lemos|2016|CSD Communication|||
description: Related Article: Leandro de O. Amaral, Viner Sousa Lima, Sérgio Macêdo Soares, Julia Bornhorst, Sebastião S. Lemos, Claudia Cristina Gatto, Robert A. Burrow, Priscila Gubert|2020|J.Organomet.Chem.|926|121500|doi:10.1016/j.jorganchem.2020.121500
DOI: 10.5517/ccdc.csd.cc130dq7
title: CCDC 1013288: Experimental Crystal Structure Determination

description: Related Article: Leandro de O. Amaral, Viner Sousa Lima, Sérgio Macêdo Soares, Julia Bornhorst, Sebastião S. Lemos, Claudia Cristina Gatto, Robert A. Burrow, Priscila Gubert|2020|J.Organomet.Chem.|926|121500|doi:10.1016/j.jorganchem.2020.121500
DOI: 10.6084/m9.figshare.12992918.v1
title: LDmatrices

description: output: This directory contains LD matrices that were used for generating the null distribution within LDna against which the 500 outlier SNP LD matrix was compared.<br>LDmat_500SNPs.txt: LD matrix for the 500 outlier Bayenv SNPs