cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7056881
title: Additional file 4: of Human Alzheimer’s disease gene expression signatures and immune profile in APP mouse models: a discrete transcriptomic view of Aβ plaque pathology

description: Table S2. Age and strain-related pathway analysis in TgCRND8 cortex. Pathways analysis showing data from upregulated network processes in TgCRND8 cortex and plaque-associated tissue. Differentially expressed genes were identified by Pearson correlation or T-test using Matlab R2010b (Mathworks). A p-value cutoff of &lt; 0.001 was used to identify differentially expressed genes. The FDR corresponding to this p-value is given in each of the comparisons to convey relative signature confidence. Set annotation analysis was performed by comparing input sets to GeneGo ( www.genego.com ), Ingenuity ( www.ingenuity.com ) and KEGG ( www.genome.jp/kegg/ ) pathway sets. Bonferroni corrected hypergeometric p-values (expectation (e)-values) of less than 0.1 were considered significant overlap between sets. (XLSX 81 kb)
DOI: 10.6084/m9.figshare.7056881.v1
title: Additional file 4: of Human Alzheimer’s disease gene expression signatures and immune profile in APP mouse models: a discrete transcriptomic view of Aβ plaque pathology

description: Table S2. Age and strain-related pathway analysis in TgCRND8 cortex. Pathways analysis showing data from upregulated network processes in TgCRND8 cortex and plaque-associated tissue. Differentially expressed genes were identified by Pearson correlation or T-test using Matlab R2010b (Mathworks). A p-value cutoff of &lt; 0.001 was used to identify differentially expressed genes. The FDR corresponding to this p-value is given in each of the comparisons to convey relative signature confidence. Set annotation analysis was performed by comparing input sets to GeneGo ( www.genego.com ), Ingenuity ( www.ingenuity.com ) and KEGG ( www.genome.jp/kegg/ ) pathway sets. Bonferroni corrected hypergeometric p-values (expectation (e)-values) of less than 0.1 were considered significant overlap between sets. (XLSX 81 kb)
DOI: 10.6084/m9.figshare.7056869
title: Additional file 3: of Human Alzheimer’s disease gene expression signatures and immune profile in APP mouse models: a discrete transcriptomic view of Aβ plaque pathology

description: Table S1. Age and strain-related transcriptomic changes in AD models. RNAseq was carried out on cortexes isolated from Tg2576 (ages: 3mo, 6mo, 9mo, 12mo and 15mo, respectively), TgCRND8 (1.5mo, 3mo, 4.5mo, 6mo and 10mo, respectively) and WT age-matched controls mice. Data shows statistical analysis of age correlation between each strain, p-value and log10 analysis. Differentially expressed genes were identified by Pearson correlation or T-test using Matlab R2010b (Mathworks). A p-value cutoff of &lt; 0.001 was used to identify differentially expressed genes. The FDR corresponding to this p-value is given in each of the comparisons to convey relative signature confidence. Set annotation analysis was performed by comparing input sets to GeneGo ( www.genego.com ), Ingenuity ( www.ingenuity.com ) and KEGG ( www.genome.jp/kegg/ ) pathway sets. Bonferroni corrected hypergeometric p-values expectation (e)-values) of less than 0.1 were considered significant overlap between sets. (XLS 7280 kb)
DOI: 10.6084/m9.figshare.7056869.v1
title: Additional file 3: of Human Alzheimer’s disease gene expression signatures and immune profile in APP mouse models: a discrete transcriptomic view of Aβ plaque pathology

description: Table S1. Age and strain-related transcriptomic changes in AD models. RNAseq was carried out on cortexes isolated from Tg2576 (ages: 3mo, 6mo, 9mo, 12mo and 15mo, respectively), TgCRND8 (1.5mo, 3mo, 4.5mo, 6mo and 10mo, respectively) and WT age-matched controls mice. Data shows statistical analysis of age correlation between each strain, p-value and log10 analysis. Differentially expressed genes were identified by Pearson correlation or T-test using Matlab R2010b (Mathworks). A p-value cutoff of &lt; 0.001 was used to identify differentially expressed genes. The FDR corresponding to this p-value is given in each of the comparisons to convey relative signature confidence. Set annotation analysis was performed by comparing input sets to GeneGo ( www.genego.com ), Ingenuity ( www.ingenuity.com ) and KEGG ( www.genome.jp/kegg/ ) pathway sets. Bonferroni corrected hypergeometric p-values expectation (e)-values) of less than 0.1 were considered significant overlap between sets. (XLS 7280 kb)
DOI: 10.6084/m9.figshare.7056860
title: MOESM1 of Personalized prescription of tyrosine kinase inhibitors in unresectable metastatic cholangiocarcinoma

description: Additional file 1: Table S1. Additional table.
DOI: 10.6084/m9.figshare.7056860.v1
title: MOESM1 of Personalized prescription of tyrosine kinase inhibitors in unresectable metastatic cholangiocarcinoma

description: Additional file 1: Table S1. Additional table.
DOI: 10.6084/m9.figshare.7056836
title: MOESM3 of Expressing the Thermoanaerobacterium saccharolyticum pforA in engineered Clostridium thermocellum improves ethanol production

description: Additional file 3. Tabular presentation of the data from fermentation of high cellulose concentrations.
DOI: 10.6084/m9.figshare.7056836.v1
title: MOESM3 of Expressing the Thermoanaerobacterium saccharolyticum pforA in engineered Clostridium thermocellum improves ethanol production

description: Additional file 3. Tabular presentation of the data from fermentation of high cellulose concentrations.
DOI: 10.6084/m9.figshare.7056827
title: Additional file 2: of Using predicate and provenance information from a knowledge graph for drug efficacy screening

description: Performance for different ratios between the positive and the negative cases in the training set. This file shows the performance on a balanced test set as a function of the ratio of positive and negative cases in the training set. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.7056827.v1
title: Additional file 2: of Using predicate and provenance information from a knowledge graph for drug efficacy screening

description: Performance for different ratios between the positive and the negative cases in the training set. This file shows the performance on a balanced test set as a function of the ratio of positive and negative cases in the training set. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.7056824
title: MOESM1 of Expressing the Thermoanaerobacterium saccharolyticum pforA in engineered Clostridium thermocellum improves ethanol production

description: Additional file 2. List of mutations observed among the strains described in this study
DOI: 10.6084/m9.figshare.7056824.v1
title: MOESM1 of Expressing the Thermoanaerobacterium saccharolyticum pforA in engineered Clostridium thermocellum improves ethanol production

description: Additional file 2. List of mutations observed among the strains described in this study
DOI: 10.6084/m9.figshare.7056800
title: Additional file 2: of Modelling the spatial distribution of aquatic insects (Order Hemiptera) potentially involved in the transmission of Mycobacterium ulcerans in Africa

description: Table S1. Recorded occurrences for the family Naucoridae. Table S2. Recorded occurrences for the Belostomatidae. Table S3. Recorded occurrences for the Notonectidae. Table S4. Recorded occurrences for the Nepidae. Table S5. Recorded occurrences for family Gerridae. Table S6. Recorded occurrences for family Corixidae. (XLSX 151 kb)
DOI: 10.6084/m9.figshare.7056800.v1
title: Additional file 2: of Modelling the spatial distribution of aquatic insects (Order Hemiptera) potentially involved in the transmission of Mycobacterium ulcerans in Africa

description: Table S1. Recorded occurrences for the family Naucoridae. Table S2. Recorded occurrences for the Belostomatidae. Table S3. Recorded occurrences for the Notonectidae. Table S4. Recorded occurrences for the Nepidae. Table S5. Recorded occurrences for family Gerridae. Table S6. Recorded occurrences for family Corixidae. (XLSX 151 kb)
DOI: 10.6084/m9.figshare.7056653
title: Sorption-Induced Deformation and Elastic Weakening of Bentheim Sandstone

description: The data is related to the article "Sorption-Induced Deformation and Elastic Weakening of Bentheim Sandstone" submitted to Journal of Geophysical Research - Solid Earth<br>The file “data.xlsx” contains processed measurements and results presented in the article<br><br>The content of data: “nn-xxRH monitoring from DATE till DATE.txt” - temperature and RH logging “nn-xxRH ultrasonic.csv” - recorded waveforms of ultrasonic signalsHere 'nn' stands for number of datapoint, 'xxRH' shows that RH value at this datapoint is equal to xx
DOI: 10.6084/m9.figshare.7056653.v1
title: Sorption-Induced Deformation and Elastic Weakening of Bentheim Sandstone

description: The data is related to the article "Sorption-Induced Deformation and Elastic Weakening of Bentheim Sandstone" submitted to Journal of Geophysical Research - Solid Earth<br>The file “data.xlsx” contains processed measurements and results presented in the article<br><br>The content of data: “nn-xxRH monitoring from DATE till DATE.txt” - temperature and RH logging “nn-xxRH ultrasonic.csv” - recorded waveforms of ultrasonic signalsHere 'nn' stands for number of datapoint, 'xxRH' shows that RH value at this datapoint is equal to xx
DOI: 10.6084/m9.figshare.7056626
title: SEC Global data

description: The folder contains maps of soil evaporation (Esmap.txt), evaporation of intercepted water (Eimap.txt) and the characteristic length (LCmap.txt) at global scale (480 x 1440 values for 120 times 360 degrees; latitude ranging from -60 to plus 60 degrees).<br>The file is organized as follows:for all 480 latitudes starting at -59.875 degrees (ending at +59.875) 1440 values for longitudes starting at coordinate -179.875 (ending at +179.875) are written (one value on each row).<br>Note that for evaporation the cumulative evaporation in mm over 8 years is given.<br>
DOI: 10.6084/m9.figshare.7056626.v1
title: Global data

description: The file contains the values of soil evaporation (eoutmap.txt), evaporation of intercepted water (intoutmap.txt) and the characterstic length (LCmap.txt) at global scale (480 x 1440 values for 120 times 360 degrees).
DOI: 10.6084/m9.figshare.7056626.v2
title: SEC Global data

description: The file contains the values of soil evaporation (eoutmap.txt), evaporation of intercepted water (intoutmap.txt) and the characterstic length (LCmap.txt) at global scale (480 x 1440 values for 120 times 360 degrees).
DOI: 10.25919/5f48e7d257312
title: Parkes observations for project P1068 semester 2020APRS_09

description: In the fast-moving world of Fast Radio Bursts (FRBs), the key question of what fraction (as high as 100%?) of FRBs emit repeat bursts remains unanswered. Of order 10 repeating FRBs are now known, and their spectro-temporal properties hint at differences with apparently non-repeating bursts - but poor statistics preclude a definitive diagnosis. FRB 180301 is a promising source for further study for multiple reasons: it is the first repeating FRB seen by the FAST telescope, and has the second-highest rotation measure ever seen for a FRB (after the original repeater, FRB121102). We request Parkes observations with the UWL to characterise the broadband emission properties of this FRB, with the following key goals: to constrain the repetition rate, identify any variation of pulse characteristics over time, and provide insight into the emission mechanisms. In its initial detection, FRB 180301 was poorly fit by regular Faraday rotation models, and showed significant circular polarization, which may indicate the progenitor is embedded in an extreme magneto-ionic environment with complex field structure that has not been seen before. These observations will generate a large data volume. We will use the Medusa backend in parallel with the Breakthrough Listen data recorder (BL), and will transfer data to BL immediately after observations.These data will be used by P. Kumar to prototype a FRB pipeline for the UWL, that will be made broadly available for similar studies.
DOI: 10.6084/m9.figshare.7056545
title: Verification Database

description: Subset of genomes from the NCBI viral database used in verification experiments in the referencing work.<br>
DOI: 10.6084/m9.figshare.7056545.v1
title: Verification Database

description: Subset of genomes from the NCBI viral database used in verification experiments in the referencing work.<br>
DOI: 10.6084/m9.figshare.7056533.v1
title: Predicted genes for Neurospora intermedia spore killers

description: Predicted genes in the genomes of three Neurospora intermedia strains.<br>See Svedberg et al., (2018) "Convergent evolution of complex genomic rearrangements in two fungal meiotic drive elements" for further information: https://www.nature.com/articles/s41467-018-06562-x (DOI:10.1038/s41467-018-06562-x)<br><br>7426, <i>Sk-2</i>3194, <i>Sk-3</i>8761, sensitive<br>Each strain is annotated separately using transcripts assembled using Cufflinks, based on RNA-seq data. The predicted genes are deposited as a GFF file, a fasta file with predicted transcipts and a fasta file with predicted proteins. The GFF file was created using the de novo assemblies also found in the following Figshare dataset: <br><br>Svedberg, et al., "PacBio based genome assemblies of Neurospora intermedia spore killer strains".<br>https://doi.org/10.6084/m9.figshare.6974033
DOI: 10.6084/m9.figshare.7056479
title: Basedatos_descargario

description: Diámetro de descarga de manglares,Diámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglares
DOI: 10.6084/m9.figshare.7056449
title: processed data for kick-out and PiSwerl experiments

description: .mat files for kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056479.v1
title: Basedatos_descargario

description: Diámetro de descarga de manglares,Diámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglaresDiámetro de descarga de manglares
DOI: 10.6084/m9.figshare.7056443
title: scripts for kick-out and PiSwerl experiment control and analysis

description: code to control and analysis kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056449.v1
title: processed data for kick-out and PiSwerl experiments

description: .mat files for kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056449.v3
title: processed data for kick-out and PiSwerl experiments

description: .mat files for kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056434
title: piswerl experiment data

description: raw dataset for piswerl tests
DOI: 10.6084/m9.figshare.7056443.v1
title: scripts for kick-out and PiSwerl experiment control and analysis

description: code to control and analysis kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056449.v2
title: processed data for kick-out and PiSwerl experiments

description: .mat files for kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056443.v3
title: scripts for kick-out and PiSwerl experiment control and analysis

description: code to control and analysis kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056443.v2
title: scripts for kick-out and PiSwerl experiment control and analysis

description: code to control and analysis kick-out tests and PiSwerl tests
DOI: 10.6084/m9.figshare.7056425
title: kick out experiment data

description: raw dataset for kick out tests
DOI: 10.6084/m9.figshare.7056434.v1
title: piswerl experiment data

description: raw dataset for piswerl tests
DOI: 10.6084/m9.figshare.7056434.v2
title: piswerl experiment data

description: raw dataset for piswerl tests
DOI: 10.6084/m9.figshare.7056413
title: scripts to process shear strength data

description: MATLAB scripts to parse raw shear force dataset
DOI: 10.6084/m9.figshare.7056425.v1
title: kick out experiment data

description: raw dataset for kick out tests
DOI: 10.6084/m9.figshare.7056425.v3
title: kick out experiment data

description: raw dataset for kick out tests
DOI: 10.6084/m9.figshare.7056413.v2
title: scripts to process shear strength data

description: MATLAB scripts to parse raw shear force dataset
DOI: 10.6084/m9.figshare.7056425.v2
title: kick out experiment data

description: raw dataset for kick out tests
DOI: 10.6084/m9.figshare.7056413.v1
title: scripts to process shear strength data

description: MATLAB scripts to parse raw shear force dataset
DOI: 10.6084/m9.figshare.7056389
title: processed shear strength data (field and lab)

description: processed shear strength for 0310 (WS-barchan), 0309 (WS-parabolics), 0109 (lab)
DOI: 10.6084/m9.figshare.7056389.v2
title: processed shear strength data (field and lab)

description: processed shear strength for 0310 (WS-barchan), 0309 (WS-parabolics), 0109 (lab)
DOI: 10.6084/m9.figshare.7056389.v1
title: processed shear strength data (field and lab)

description: processed shear strength for 0310 (WS-barchan), 0309 (WS-parabolics), 0109 (lab)
DOI: 10.6084/m9.figshare.7056401.v1
title: Semiparametric Regression using Variational Approximations

description: Semiparametric regression offers a flexible framework for modeling non-linear relationships between a response and covariates. A prime example are generalized additive models where splines (say) are used to approximate non-linear functional components in conjunction with a quadratic penalty to control for overfitting. Estimation and inference are then generally performed based on the penalized likelihood, or under a mixed model framework. The penalized likelihood framework is fast but potentially unstable, and choosing the smoothing parameters needs to be done externally using cross-validation, for instance. The mixed model framework tends to be more stable and offers a natural way for choosing the smoothing parameters, but for non-normal responses involves an intractable integral. In this article, we introduce a new framework for semiparametric regression based on variational approximations. The approach possesses the stability and natural inference tools of the mixed model framework, while achieving computation times comparable to using penalized likelihood. Focusing on generalized additive models, we derive fully tractable variational likelihoods for some common response types. We present several features of the variational approximation framework for inference, including a variational information matrix for inference on parametric components, and a closed-form update for estimating the smoothing parameter. We demonstrate the consistency of the variational approximation estimates, and an asymptotic normality result for the parametric component of the model. Simulation studies show the variational approximation framework performs similarly to and sometimes better than currently available software for fitting generalized additive models.
DOI: 10.6084/m9.figshare.7056380
title: Shear strength data (laboratory)

description: Shear force measurements in laboratory on Jan 9, 2017
DOI: 10.6084/m9.figshare.7056380.v2
title: Shear strength data (laboratory)

description: Shear force measurements in laboratory on Jan 9, 2017
DOI: 10.6084/m9.figshare.7056380.v1
title: Shear strength data (laboratory)

description: Shear force measurements in laboratory on Jan 9, 2017
DOI: 10.6084/m9.figshare.7056350
title: Shear strength data (WhiteSands - barchan)

description: Shear force measurements at White Sands barchan dune on March 10, 2017
DOI: 10.6084/m9.figshare.7056353
title: Shear strength data (WhiteSands - parabolics)

description: Shear force measurements at White Sands parabolic dune on March 9, 2017
DOI: 10.6084/m9.figshare.7056353.v2
title: Shear strength data (WhiteSands - parabolics)

description: Shear force measurements at White Sands parabolic dune on March 9, 2017
DOI: 10.6084/m9.figshare.7056350.v1
title: Shear strength data (WhiteSands - barchan)

description: Shear force measurements at White Sands barchan dune on March 10, 2017
DOI: 10.6084/m9.figshare.7056350.v2
title: Shear strength data (WhiteSands - barchan)

description: Shear force measurements at White Sands barchan dune on March 10, 2017
DOI: 10.6084/m9.figshare.7056353.v1
title: Shear strength data (WhiteSands - parabolics)

description: Shear force measurements at White Sands parabolic dune on March 9, 2017
DOI: 10.6084/m9.figshare.7056347
title: Observer cjz

description: The instructions how to use this data set are available in a text file titled 'The relative contribution of color and material in object selection.txt' which can be found at https://github.com/BrainardLab/ColorMaterial .
DOI: 10.6084/m9.figshare.7056347.v1
title: Observer cjz

description: The instructions how to use this data set are available in a text file titled 'The relative contribution of color and material in object selection.txt' which can be found at https://github.com/BrainardLab/ColorMaterial .
DOI: 10.6084/m9.figshare.7056266
title: Siemann et al Monkfish data scallop survey Georges Bank.csv

description: Data set accompanying paper published on seasonal changes in monkfish relative abundance on Georges Bank
DOI: 10.6084/m9.figshare.7056266.v1
title: Siemann et al Monkfish data scallop survey Georges Bank.csv

description: Data set accompanying paper published on seasonal changes in monkfish relative abundance on Georges Bank
DOI: 10.6084/m9.figshare.7056161.v1
title: A Sustainable Collaboratory for Coastal Resilience Research

description: Our goal is to create a cloud-ready repository of open-source coastal modeling tools which enable scientists and engineers to use high performance computers to study a variety of physical and ecological processes. The system we are building leverages Jupyter notebooks, Docker, Singularity, and the Agave Platform to create a platform for running jobs and analyzing data in a way that is (1) intuitive, (2) repeatable, (3) and collaborative. The paper describes the methodology to integrate the four technologies into the system that serves the coastal resilience research collaboratory. Two commonly used open-source numer- ical models are used to demonstrate the utility of the system. Simulation results of ocean waves generated by Hurricane Issac (2012) and coastal wave evolution are presented as an illustration. The sustainability of the collaboratory is discussed in detail.
DOI: 10.6084/m9.figshare.7054565
title: draft v1

description: Laser surface texturing for interference fit
DOI: 10.6084/m9.figshare.7054523
title: Leptoxis ampla population genomics

description: These data include processed SNP data in various formats for Leptoxis ampla and shell photographs of L. ampla used for geometric morphometrics. Genetic data is presented in formats used for multiple analyses in the study (e.g., vcf), and some methods have data (genetic and locality) specific to a program used for analyses. Details about data generation can be found in the associated manuscript.
DOI: 10.6084/m9.figshare.7054496
title: Supplementary tables.docx

description: Correlation among minerals of four varieties of mexican Ayocote beansCorrelation among total phenolic, total flavonoids, total anthocyanins and antioxidant assays (DPPH and ORAC) of four varieties of mexican Ayocote bean
DOI: 10.6084/m9.figshare.7054496.v1
title: Supplementary tables.docx

description: Correlation among minerals of four varieties of mexican Ayocote beansCorrelation among total phenolic, total flavonoids, total anthocyanins and antioxidant assays (DPPH and ORAC) of four varieties of mexican Ayocote bean