cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13204478.v1
title: Additional file 10 of Genomic analysis of circular RNAs in heart

description: Additional file 10. Table S5. List of high-confidence and significantly dysregulated circRNAs in DCM compared to normal heart samples. Chromosome coordinates are in hg38 annotation. The threshold for significance was p &lt;0.05 and fold change &gt; 2.
DOI: 10.6084/m9.figshare.13204502.v1
title: Additional file 3 of Genomic analysis of circular RNAs in heart

description: Additional file 3. Table S2. Primers used for validation of the mouse ortholog of selected human circRNAs. Mouse Yap1 primers were used as internal control for PCR reaction using genomic DNA.
DOI: 10.6084/m9.figshare.13204511
title: Additional file 6 of Genomic analysis of circular RNAs in heart

description: Additional file 6. Table S4. List of circRNAs originated from two different genes in 10 human heart samples. Chromosome coordinates are in hg38 annotation. In the last column, “yes” indicates that the circRNA is from two neighboring genes with highly similar sequence, and “no” indicates no sequence similarity was observed and the circRNA is likely a bona fide rt-circRNA.
DOI: 10.6084/m9.figshare.13204508.v1
title: Additional file 5 of Genomic analysis of circular RNAs in heart

description: Additional file 5. Table S3. Information of the 20,214 circRNAs identified in this study. Chromosome coordinates are in hg38 annotation.
DOI: 10.6084/m9.figshare.13204490
title: Additional file 14 of Genomic analysis of circular RNAs in heart

description: Additional file 14. Table S7. Predicted targets of heart disease-related miRNAs. The targeted genes of each miRNA were obtained from TargetScan ( http://www.targetscan.org/vert_72/ ). The significance of changes of targeted genes in DCM compared to normal samples were determined by DESeq2 with threshold of fold change &gt;2 and FDR &lt;0.05. A total of 937 and 480 genes were identified to be significantly up- and down-regulated in DCM, respectively.
DOI: 10.6084/m9.figshare.13204508
title: Additional file 5 of Genomic analysis of circular RNAs in heart

description: Additional file 5. Table S3. Information of the 20,214 circRNAs identified in this study. Chromosome coordinates are in hg38 annotation.
DOI: 10.6084/m9.figshare.13204630
title: Additional file 5 of Precise levels of nectin-3 are required for proper synapse formation in postnatal visual cortex

description: Additional file 5. Summary of all statistical analyses and p values for comparisons between condition, ages, and dendrite type. The type of analysis as well as the Bonferroni critical value used to establish significance, are indicated. Whether the data was first transformed to correct for non-normality or heteroskedasticity is also indicated, and final p values for Shapiro and Levine tests (after any necessary data transformations) are shown. An additional sheet labeled ‘Metadata’ documents the number of animals and dendrites sampled for each condition. This sheet also includes p values describing individual t-test comparisons of apical and basal dendrites for each condition.
DOI: 10.6084/m9.figshare.13204630.v1
title: Additional file 5 of Precise levels of nectin-3 are required for proper synapse formation in postnatal visual cortex

description: Additional file 5. Summary of all statistical analyses and p values for comparisons between condition, ages, and dendrite type. The type of analysis as well as the Bonferroni critical value used to establish significance, are indicated. Whether the data was first transformed to correct for non-normality or heteroskedasticity is also indicated, and final p values for Shapiro and Levine tests (after any necessary data transformations) are shown. An additional sheet labeled ‘Metadata’ documents the number of animals and dendrites sampled for each condition. This sheet also includes p values describing individual t-test comparisons of apical and basal dendrites for each condition.
DOI: 10.6084/m9.figshare.13204658.v1
title: Additional file 1 of Trace element distribution in human cortical bone microstructure: the potential for unravelling diet and social status in archaeological bones

description: Additional file 1. The concentrations of Sr, Ba, Cu, and Pb for each of the scored structures, laminar bone, 1st, 2nd, or 3rd generation osteons, as well as their coordinates in the cross-sections analyzed.
DOI: 10.6084/m9.figshare.13204661
title: Additional file 2 of Trace element distribution in human cortical bone microstructure: the potential for unravelling diet and social status in archaeological bones

description: Additional file 2. Spearman correlation matrix.
DOI: 10.6084/m9.figshare.13204664.v1
title: Additional file 3 of Trace element distribution in human cortical bone microstructure: the potential for unravelling diet and social status in archaeological bones

description: Additional file 3. Means, relative standard deviations, and relative standard deviations (RSD) for each bone microstructure category for each individual.
DOI: 10.6084/m9.figshare.13204658
title: Additional file 1 of Trace element distribution in human cortical bone microstructure: the potential for unravelling diet and social status in archaeological bones

description: Additional file 1. The concentrations of Sr, Ba, Cu, and Pb for each of the scored structures, laminar bone, 1st, 2nd, or 3rd generation osteons, as well as their coordinates in the cross-sections analyzed.
DOI: 10.6084/m9.figshare.13204664
title: Additional file 3 of Trace element distribution in human cortical bone microstructure: the potential for unravelling diet and social status in archaeological bones

description: Additional file 3. Means, relative standard deviations, and relative standard deviations (RSD) for each bone microstructure category for each individual.
DOI: 10.6084/m9.figshare.13204661.v1
title: Additional file 2 of Trace element distribution in human cortical bone microstructure: the potential for unravelling diet and social status in archaeological bones

description: Additional file 2. Spearman correlation matrix.
DOI: 10.6084/m9.figshare.13204688
title: Additional file 12 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 12: Table S5. Coding DEGs-CP vs. N: This table shows the list of coding DEGs in Chronic Pancreatitis tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204697
title: Additional file 15 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 15: Table S8. Non-Coding DEGs-CP vs. N: This table shows the list of non-coding DEGs in Chronic Pancreatitis tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204685
title: Additional file 11 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 11: Table S4. Coding DEGs-PC vs. N: This table shows the list of coding DEGs in Pancreatic cancer tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204685.v1
title: Additional file 11 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 11: Table S4. Coding DEGs-PC vs. N: This table shows the list of coding DEGs in Pancreatic cancer tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204691.v1
title: Additional file 13 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 13: Table S6. Coding DEGs-PC vs. CP: This table shows the list of coding DEGs in Pancreatic cancer tissues as compared to Chronic Pancreatitis tissues
DOI: 10.6084/m9.figshare.13204697.v1
title: Additional file 15 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 15: Table S8. Non-Coding DEGs-CP vs. N: This table shows the list of non-coding DEGs in Chronic Pancreatitis tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204700.v1
title: Additional file 16 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 16: Table S9. Non-Coding DEGs-PC vs. CP: This table shows the list of non-coding DEGs in Pancreatic cancer tissues as compared to Chronic Pancreatitis tissues
DOI: 10.6084/m9.figshare.13204694
title: Additional file 14 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 14: Table S7. Non-Coding DEGs-PC vs. N: This table shows the list of non-coding DEGs in Pancreatic cancer tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204700
title: Additional file 16 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 16: Table S9. Non-Coding DEGs-PC vs. CP: This table shows the list of non-coding DEGs in Pancreatic cancer tissues as compared to Chronic Pancreatitis tissues
DOI: 10.6084/m9.figshare.13204691
title: Additional file 13 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 13: Table S6. Coding DEGs-PC vs. CP: This table shows the list of coding DEGs in Pancreatic cancer tissues as compared to Chronic Pancreatitis tissues
DOI: 10.6084/m9.figshare.13204694.v1
title: Additional file 14 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 14: Table S7. Non-Coding DEGs-PC vs. N: This table shows the list of non-coding DEGs in Pancreatic cancer tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204706
title: Additional file 18 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 18: Table S10. Functional Annotation of genes: This table shows the functional annotation of malignancy specific genes.
DOI: 10.6084/m9.figshare.13204706.v1
title: Additional file 18 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 18: Table S10. Functional Annotation of genes: This table shows the functional annotation of malignancy specific genes.
DOI: 10.6084/m9.figshare.13204688.v1
title: Additional file 12 of Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

description: Additional file 12: Table S5. Coding DEGs-CP vs. N: This table shows the list of coding DEGs in Chronic Pancreatitis tissues as compared to Normal tissues
DOI: 10.6084/m9.figshare.13204747
title: Additional file 12 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 12. Supplementary Table S11.
DOI: 10.6084/m9.figshare.13204741.v1
title: Additional file 10 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 10. Supplementary Table S9.
DOI: 10.6084/m9.figshare.13204759.v1
title: Additional file 4 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 4. Supplementary Table S3.
DOI: 10.6084/m9.figshare.13204744.v1
title: Additional file 11 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 11. Supplementary Table S10.
DOI: 10.6084/m9.figshare.13204744
title: Additional file 11 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 11. Supplementary Table S10.
DOI: 10.6084/m9.figshare.13204741
title: Additional file 10 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 10. Supplementary Table S9.
DOI: 10.6084/m9.figshare.13204756
title: Additional file 3 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 3. Supplementary Table S2.
DOI: 10.6084/m9.figshare.13204759
title: Additional file 4 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 4. Supplementary Table S3.
DOI: 10.6084/m9.figshare.13204774.v1
title: Additional file 9 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 9. Supplementary Table S8.
DOI: 10.6084/m9.figshare.13204765.v1
title: Additional file 6 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 6. Supplementary Table S5.
DOI: 10.6084/m9.figshare.13204768.v1
title: Additional file 7 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 7. Supplementary Table S6.
DOI: 10.6084/m9.figshare.13204756.v1
title: Additional file 3 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 3. Supplementary Table S2.
DOI: 10.6084/m9.figshare.13204753
title: Additional file 2 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 2. Supplementary Table S1.
DOI: 10.6084/m9.figshare.13204753.v1
title: Additional file 2 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 2. Supplementary Table S1.
DOI: 10.6084/m9.figshare.13204762
title: Additional file 5 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 5. Supplementary Table S4.
DOI: 10.6084/m9.figshare.13204771.v1
title: Additional file 8 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 8. Supplementary Table S7.
DOI: 10.6084/m9.figshare.13204762.v1
title: Additional file 5 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 5. Supplementary Table S4.
DOI: 10.6084/m9.figshare.13204747.v1
title: Additional file 12 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 12. Supplementary Table S11.
DOI: 10.6084/m9.figshare.13204768
title: Additional file 7 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 7. Supplementary Table S6.
DOI: 10.6084/m9.figshare.13204765
title: Additional file 6 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 6. Supplementary Table S5.
DOI: 10.6084/m9.figshare.13204774
title: Additional file 9 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 9. Supplementary Table S8.
DOI: 10.6084/m9.figshare.13204771
title: Additional file 8 of Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

description: Additional file 8. Supplementary Table S7.
DOI: 10.5281/zenodo.4249707
title: Predicting Nanoparticle Uptake by Biological Membranes: Theory and Simulation - data

description: Simulation data described in paper entitled "Predicting Nanoparticle Uptake by Biological Membranes: Theory and Simulation"
DOI: 10.5281/zenodo.4249706
title: Predicting Nanoparticle Uptake by Biological Membranes: Theory and Simulation - data

description: Simulation data described in paper entitled "Predicting Nanoparticle Uptake by Biological Membranes: Theory and Simulation"
DOI: 10.15161/oar.it/73239
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.4260659
title: Características e Imágenes de los Smartphones en venta en Amazon

description: Características e Imágenes de los Smartphones en venta en Amazon. (datos simulados, no pertenecen a Amazon)
DOI: 10.5281/zenodo.4260658
title: Características e Imágenes de los Smartphones en venta en Amazon

description: Características e Imágenes de los Smartphones en venta en Amazon. (datos simulados, no pertenecen a Amazon)
DOI: 10.25919/5fa7c7fc76626
title: Parkes observations for project P1068 semester 2020APRS_24

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: 10.5281/zenodo.4260703
title: historico indices mercado hipotecario y vivienda de españa

description: Serie histórica integrada por los índices de referencia del mercado hipotecario español (EURIBOR, MIBOR, …) publicados por la AHE en su página web. Dicha asociación se encarga de recopilar esta la información de estas series publicadas por diferentes instituciones (BCE, BdE, …). Por otro lado, se ha agregado al dataset información publicada por INE y el Ministerio de Vivienda relativas a la evolución del mercado de la vivienda (número de compraventa mensual de viviendas, precio medio de la vivienda, …).
DOI: 10.5281/zenodo.4260702
title: historico indices mercado hipotecario y vivienda de españa

description: Serie histórica integrada por los índices de referencia del mercado hipotecario español (EURIBOR, MIBOR, …) publicados por la AHE en su página web. Dicha asociación se encarga de recopilar esta la información de estas series publicadas por diferentes instituciones (BCE, BdE, …). Por otro lado, se ha agregado al dataset información publicada por INE y el Ministerio de Vivienda relativas a la evolución del mercado de la vivienda (número de compraventa mensual de viviendas, precio medio de la vivienda, …).
DOI: 10.5517/ccdc.csd.cc26782t
title: CCDC 2032765: Experimental Crystal Structure Determination

description: Related Article: Anand H. Shinde, Shyam Sathyamoorthi|2020|Org.Lett.|22|8665|doi:10.1021/acs.orglett.0c03257
DOI: 10.5281/zenodo.4081424
title: alpha Synuclein PIFE HDF5 files and analyses

description: smPIFE measurements of the alpha Synuclein monomer and of ssDNA & dsDNA - analysis documentation (Jupyter notebook) and raw data files (photon HDF5).
DOI: 10.5281/zenodo.4081423
title: alpha Synuclein PIFE HDF5 files and analyses

description: smPIFE measurements of the alpha Synuclein monomer and of ssDNA & dsDNA - analysis documentation (Jupyter notebook) and raw data files (photon HDF5).
DOI: 10.5281/zenodo.4261101
title: Fast Fashion Eco Commitment Dataset

description: This dataset contains intormation on prices, composition and "eco tagging" (i.e. being marketed as an eco friendly product) for 277 items in the Spanish Zara catalogue (Inditex group) as retrieved from their webside on 2020-11-07. Further, the dataset is structured in two dimensions: Items Dimension (on row per item): 'item_code': primary key. Numeric code assigned to each clothin item 'item_name': str, name of the item. 'item_desc': str, description of the item. 'join_life': bool, weather or not the item is eco-tagged 'joinlife_title': str, ecologic marking 'joinlife_desc': str, description of the ecologic action taken 'item_price': num, price of the item in cents of € Composition Dimension (one row per clothing material): 'item_code': int, foreign key to merge with Items Dimention 'part_name': str, part of the clothing item (e.g. Inside/Outside) 'material': str, name of the material. 'percent': srt, percentage of the material realtive to the clothing part. Disclaimer: This dataset was created within the framework of Univeristat Oberta de Catalunya's Msc in Data Science as a research project and its purpose is purely educational.
DOI: 10.5281/zenodo.4261100
title: Fast Fashion Eco Commitment Dataset

description: This dataset contains intormation on prices, composition and "eco tagging" (i.e. being marketed as an eco friendly product) for 277 items in the Spanish Zara catalogue (Inditex group) as retrieved from their webside on 2020-11-07. Further, the dataset is structured in two dimensions: Items Dimension (on row per item): 'item_code': primary key. Numeric code assigned to each clothin item 'item_name': str, name of the item. 'item_desc': str, description of the item. 'join_life': bool, weather or not the item is eco-tagged 'joinlife_title': str, ecologic marking 'joinlife_desc': str, description of the ecologic action taken 'item_price': num, price of the item in cents of € Composition Dimension (one row per clothing material): 'item_code': int, foreign key to merge with Items Dimention 'part_name': str, part of the clothing item (e.g. Inside/Outside) 'material': str, name of the material. 'percent': srt, percentage of the material realtive to the clothing part. Disclaimer: This dataset was created within the framework of Univeristat Oberta de Catalunya's Msc in Data Science as a research project and its purpose is purely educational.
DOI: 10.17632/t5x3gpmrgj.2
title: Data for: A Computational Model for Understanding the Oligomerization Mechanisms of TNF Receptor Superfamily

description: The zip file contains the snapshots taken from the trajectory of kinetic Monte-Carlo simulation for TNF receptor oligomerization.