cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/47wz7bmnnd.1
title: Knowledge absorption capacity in the innovation process

description: The tabular data contains several variables and indicators related to the study of absorptive capacity in the innovation process. The table presents data on variables including patents, the R&D investment composite index, the rate of change in government subsidies, and the net growth rate of capitalized development expenditures, as well as independent, mediating, moderating and dependent variables. The data are categorized by year to explore how different factors in innovation activities affect innovation capabilities or outcomes. The data are richly structured and cover multidimensional indicators such as R&D efficiency and financial health index, which are suitable for quantitative analysis of the innovation process.
DOI: 10.7483/opendata.cms.sttg.i8t5
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17632/m5c4n8z4bz.1
title: SVAR_CEE_2025

description: The dataset corresponds to the paper "Macroeconomic Consequences of the war in Ukraine on Central and Eastern European economies: A SVAR analysis" that investigates the macroeconomic effects from the Russian invasion of Ukraine in February 2022 on the economies of Bulgaria, Czechia, Hungary, Poland and Romania.
DOI: 10.7483/opendata.cms.epdp.9ggg
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH125_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17632/66tm6y6jzw.1
title: The Dual Effects of Population Mobility on the Rural Health Economy

description: The header of the table contains a number of composite indicators related to economic and social development. Covering a wide range of fields such as economy, industry, agriculture, transportation, health, employment, etc., they provide statistical analysis data of different dimensions, which serve as references for comprehensive evaluation and decision-making support for regions or industries.
DOI: 10.17044/scilifelab.14932062
title: WGS in familial chronic lymphocytic leukemia

description: <b>Data Set Description</b><br><br>This repository contains data from a study of three families in which two or more siblings developed chronic lymphocytic leukemia (CLL). Informed consent was provided in accordance with the declaration of Helsinki and the study was approved by the hospital medical ethics committee (METC2015-741).<br>The data consists of BAM-files from whole-genome sequencing (WGS) of nine individuals with data from tumor and matched normal tissue. WGS libraries where prepared using the TruSeq Nano Kit (Illumina Inc.) and sequenced in paired-end mode (2x150bp) on the Illumina HiSeqX Ten system (Illumina Inc.) with 30x target coverage. Reads from each library were aligned to the Grch37 reference genome using BWA mem and merged and de-duplicated using Picard. Re-alignment around known and novel indel-sites was performed with GATK. All SAM/BAM-conversion steps were completed using SAMtools.<br>The repository also contains results from Sanger sequencing of the immunoglobulin rearrangements from the tumor samples.<br>The data is under restricted access and can be accessed upon request through the email-adress below.<br><b>Terms for access</b>The WGS datasets are only to be used for research aimed at advancing the understanding of genetic factors in the development of familial chronic lymphocytic leukemia. Applications aimed at method development including bioinformatics would not be considered as acceptable for use of this dataset. <br><br>
DOI: 10.17044/scilifelab.14932062.v1
title: WGS in familial chronic lymphocytic leukemia

description: <b>Data Set Description</b><br><br>This repository contains data from a study of three families in which two or more siblings developed chronic lymphocytic leukemia (CLL). Informed consent was provided in accordance with the declaration of Helsinki and the study was approved by the hospital medical ethics committee (METC2015-741).<br>The data consists of BAM-files from whole-genome sequencing (WGS) of nine individuals with data from tumor and matched normal tissue. WGS libraries where prepared using the TruSeq Nano Kit (Illumina Inc.) and sequenced in paired-end mode (2x150bp) on the Illumina HiSeqX Ten system (Illumina Inc.) with 30x target coverage. Reads from each library were aligned to the Grch37 reference genome using BWA mem and merged and de-duplicated using Picard. Re-alignment around known and novel indel-sites was performed with GATK. All SAM/BAM-conversion steps were completed using SAMtools.<br>The repository also contains results from Sanger sequencing of the immunoglobulin rearrangements from the tumor samples.<br>The data is under restricted access and can be accessed upon request through the email-adress below.<br><b>Terms for access</b>The WGS datasets are only to be used for research aimed at advancing the understanding of genetic factors in the development of familial chronic lymphocytic leukemia. Applications aimed at method development including bioinformatics would not be considered as acceptable for use of this dataset. <br><br>
DOI: 10.7483/opendata.cms.t1cl.e1o8
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17632/rv6dxjj7j8.1
title: Data for Artificial vegetation restoration patterns regulated soil multi-functionality via co-occurrence network complexity of multitrophic biology in degraded karst region

description: Soil diversity,soil fuctions
DOI: 10.17044/scilifelab.15082398
title: Single Cell Smart-Seq 3 RNA-Seq and Bulk Exome Seq from Breast Cancer Patients

description: <b>Data Set Description</b><b><br></b>Single cell RNA sequencing (Samrt-Seq3) and Whole exome sequencing from multiple regions of individual tumors from Breast Cancer patients and also single cell RNA seq for two ovarian cancer cell lines.<br>The dataset contains raw sequencing data for various high-throughput molecular tests performed on two sample types: tumor samples from two breast cancer patients and cell lines derived from High-grade serous carcinoma Patients. <br><br>The breast cancer data comes from two patients: patient 1 (BCSA1) has two tumor regions A-B and patient 2 (BCSA2) has five regions(A-E). For a normal sample and each region from each patient Whole Exome Sequencing was performed using Twist Biosciences Human Exome Kit by the SNP&SEQ Technology platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. Also for each patient, EPCAM+ CD45- sorted cells from all the regions where sorted to a 384 well plate, and Smart-Seq3 libraries were prepared at Karolinska Institutet and sequenced at National Genomics Infrastructure Uppsala, Sweden.<br>The HGSOC cell-line data comes from OV2295R2 and TOV2295R cell lines described in Laks et al <br>Cell 2019 Nov 14; 179(5): 1207–1221.e22 doi: 10.1016/j.cell.2019.10.026 . The cell line Smart-Seq3 libraries were prepared from two 384 well plates at Karolinska Institutet and <br>sequenced at National Genomics Infrastructure Uppsala, Sweden.<br><b>Terms for access</b>This dataset is to be used for research on intratumor heterogeneity and subclonal evolution of tumors. To apply for conditional access to the dataset in this publication, please contact datacentre@scilifelab.se.<br><br><br>
DOI: 10.17044/scilifelab.15082398.v1
title: Single Cell Smart-Seq 3 RNA-Seq and Bulk Exome Seq from Breast Cancer Patients

description: <b>Data Set Description</b><b><br></b>Single cell RNA sequencing (Samrt-Seq3) and Whole exome sequencing from multiple regions of individual tumors from Breast Cancer patients and also single cell RNA seq for two ovarian cancer cell lines.<br>The dataset contains raw sequencing data for various high-throughput molecular tests performed on two sample types: tumor samples from two breast cancer patients and cell lines derived from High-grade serous carcinoma Patients. <br><br>The breast cancer data comes from two patients: patient 1 (BCSA1) has two tumor regions A-B and patient 2 (BCSA2) has five regions(A-E). For a normal sample and each region from each patient Whole Exome Sequencing was performed using Twist Biosciences Human Exome Kit by the SNP&SEQ Technology platform, SciLifeLab, National Genomics Infrastructure Uppsala, Sweden. Also for each patient, EPCAM+ CD45- sorted cells from all the regions where sorted to a 384 well plate, and Smart-Seq3 libraries were prepared at Karolinska Institutet and sequenced at National Genomics Infrastructure Uppsala, Sweden.<br>The HGSOC cell-line data comes from OV2295R2 and TOV2295R cell lines described in Laks et al <br>Cell 2019 Nov 14; 179(5): 1207–1221.e22 doi: 10.1016/j.cell.2019.10.026 . The cell line Smart-Seq3 libraries were prepared from two 384 well plates at Karolinska Institutet and <br>sequenced at National Genomics Infrastructure Uppsala, Sweden.<br><b>Terms for access</b>This dataset is to be used for research on intratumor heterogeneity and subclonal evolution of tumors. To apply for conditional access to the dataset in this publication, please contact datacentre@scilifelab.se.<br><br><br>
DOI: 10.7483/opendata.cms.ddn5.d906
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH150_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17632/rnnj3f6nvn.1
title: county economy

description: The tables contain a large amount of data related to economic, social and demographic statistics covering a wide range of indicators and variables. The data also include statistical information on specific areas, such as the number of enterprises, the number of patent applications and the number of active patents. The data reflect in detail various aspects of regional economic development, social security, infrastructure development and demographics, and are suitable for economic development studies, policy analysis and comparative regional studies.
DOI: 10.17044/scilifelab.15134739
title: Detailed feature profile of MapToCleave processed and unprocessed miRNA precursors

description: This is the Supplemental Data 6 of the MapToCleave study. <br>The file folder contains detailed feature information of MapToCleave processed and unprocessed miRNA precursors. There are seven feature files for each miRNA precursor. The file with the suffix “.HEK.statistics” provides basic information on the hairpin. The file with the suffix “.fold” provides RNA secondary structure in dot bracket format predicted by RNAfold. The file with the suffix “.str” provides printed RNA secondary structure in txt format. The file with suffix “.HEK.unopened_5p_ref” and “.HEK.unopened_3p_ref” provides positional information of base pairing indicated by “-” and symmetric mismatch bulge indicated by “*”, “&gt;” asymmetric bulge with more nucleotides at the 5p strand or “&lt;” asymmetric bulge with more nucleotides at the 3p strand. The file with suffix “.HEK.bulgefeatures_unopened_5p_ref” and “.HEK.bulgefeatures_unopened_3p_ref” provides detailed information on bulges with columns for identity, bulge name, maximum size of the bulge, start position of the bulge, end position of the bulge, type of bulge, nucleotides at the 5p strand, nucleotides at the 3p strand, the adjacent base pair at the 5’ side of the bulge and the adjacent base pair at the 3’ side of the bulge. The 5p and 3p in the file names mean that the features are counted respectively at the 5p and 3p strand of the hairpin. All the features were counted based on the 5’ side of Drosha cleavage site.<br>
DOI: 10.17044/scilifelab.15134739.v1
title: Detailed feature profile of MapToCleave processed and unprocessed miRNA precursors

description: This is the Supplemental Data 6 of the MapToCleave study. <br>The file folder contains detailed feature information of MapToCleave processed and unprocessed miRNA precursors. There are seven feature files for each miRNA precursor. The file with the suffix “.HEK.statistics” provides basic information on the hairpin. The file with the suffix “.fold” provides RNA secondary structure in dot bracket format predicted by RNAfold. The file with the suffix “.str” provides printed RNA secondary structure in txt format. The file with suffix “.HEK.unopened_5p_ref” and “.HEK.unopened_3p_ref” provides positional information of base pairing indicated by “-” and symmetric mismatch bulge indicated by “*”, “&gt;” asymmetric bulge with more nucleotides at the 5p strand or “&lt;” asymmetric bulge with more nucleotides at the 3p strand. The file with suffix “.HEK.bulgefeatures_unopened_5p_ref” and “.HEK.bulgefeatures_unopened_3p_ref” provides detailed information on bulges with columns for identity, bulge name, maximum size of the bulge, start position of the bulge, end position of the bulge, type of bulge, nucleotides at the 5p strand, nucleotides at the 3p strand, the adjacent base pair at the 5’ side of the bulge and the adjacent base pair at the 3’ side of the bulge. The 5p and 3p in the file names mean that the features are counted respectively at the 5p and 3p strand of the hairpin. All the features were counted based on the 5’ side of Drosha cleavage site.<br>
DOI: 10.17044/scilifelab.15134862
title: Detailed feature profile of MirGeneDB highly and lowly expressed miRNA precursors

description: This is the Supplementary Data 9 of the MapToCleave study. ​​The file folder contains detailed feature information of MirGeneDB highly and lowly expressed miRNA precursors of 20 species. There are six feature files for each miRNA precursor. The file with the suffix “.statistics” provides basic information on the hairpin. The file with the suffix “.fold” provides RNA secondary structure in dot bracket format predicted by RNAfold. The file with suffix “.unopened_5p_ref” and “.unopened_3p_ref” provides positional information of base pairing indicated by “-” and symmetric mismatch bulge indicated by “*”, “&gt;” asymmetric bulge with more nucleotides at the 5p strand or “&lt;” asymmetric bulge with more nucleotides at the 3p strand. The file with suffix “.bulgefeatures_unopened_5p_ref” and “.bulgefeatures_unopened_3p_ref” provides detailed information on bulges with columns for identity, bulge name, maximum size of the bulge, start position of the bulge, end position of the bulge, type of bulge, nucleotides at the 5p strand, nucleotides at the 3p strand, the adjacent base pair at the 5’ side of the bulge and the adjacent base pair at the 3’ side of the bulge. The 5p and 3p in the file names mean that the features are counted respectively at the 5p and 3p strand of the hairpin. All the features were counted based on the 5’ side of Drosha cleavage site annotated from MirGeneDB.<br>The identify information of the highly and lowly expressed MirGeneDB miRNAs are available at “in_vivo_highly_expressed_miRNA_precursor_IDs.txt” and “in_vivo_lowly_expressed_miRNA_precursor_IDs.txt” respectively. The data frame of 7-mer window free energy used for Figure 4C-D is available at “local_free_energy_7-mer_of_MirGeneDB_miRNA_precursors.txt” with columns showing the position relative to 5’ side of Drosha cleavage site and rows showing MirGeneDB ID. <br> <br>
DOI: 10.17632/g2mxr92m8f.2
title: SLR_GenerativeAI_based_PdM_Aviation

description: This dataset belongs to Systematic Literature Review (SLR) conducted on 'Generative AI based predictive maintenance in aviation industry'. The preprint of paper is available at https://doi.org/10.21203/rs.3.rs-5277729/v1
DOI: 10.17044/scilifelab.15134862.v1
title: Detailed feature profile of MirGeneDB highly and lowly expressed miRNA precursors

description: This is the Supplementary Data 9 of the MapToCleave study. ​​The file folder contains detailed feature information of MirGeneDB highly and lowly expressed miRNA precursors of 20 species. There are six feature files for each miRNA precursor. The file with the suffix “.statistics” provides basic information on the hairpin. The file with the suffix “.fold” provides RNA secondary structure in dot bracket format predicted by RNAfold. The file with suffix “.unopened_5p_ref” and “.unopened_3p_ref” provides positional information of base pairing indicated by “-” and symmetric mismatch bulge indicated by “*”, “&gt;” asymmetric bulge with more nucleotides at the 5p strand or “&lt;” asymmetric bulge with more nucleotides at the 3p strand. The file with suffix “.bulgefeatures_unopened_5p_ref” and “.bulgefeatures_unopened_3p_ref” provides detailed information on bulges with columns for identity, bulge name, maximum size of the bulge, start position of the bulge, end position of the bulge, type of bulge, nucleotides at the 5p strand, nucleotides at the 3p strand, the adjacent base pair at the 5’ side of the bulge and the adjacent base pair at the 3’ side of the bulge. The 5p and 3p in the file names mean that the features are counted respectively at the 5p and 3p strand of the hairpin. All the features were counted based on the 5’ side of Drosha cleavage site annotated from MirGeneDB.<br>The identify information of the highly and lowly expressed MirGeneDB miRNAs are available at “in_vivo_highly_expressed_miRNA_precursor_IDs.txt” and “in_vivo_lowly_expressed_miRNA_precursor_IDs.txt” respectively. The data frame of 7-mer window free energy used for Figure 4C-D is available at “local_free_energy_7-mer_of_MirGeneDB_miRNA_precursors.txt” with columns showing the position relative to 5’ side of Drosha cleavage site and rows showing MirGeneDB ID. <br> <br>
DOI: 10.7483/opendata.cms.h388.lg8e
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH175_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.17044/scilifelab.15144339
title: GHG feature profiling with multiple definitions

description: This is the Supplemental Data 13 of the MapToCleave study. <br>This dataset is related to Figure 6E. The GHG feature is profiled based on the different definitions that are described in the method section “Identifying the presence of the GHG feature using different definitions”. The file “GHG_feature_MapToCleave.txt” shows the presence of the GHG features in the MapToCleave processed and unprocessed miRNA precursors. The file “GHG_feature_MirGeneDB.txt” shows the presence of the GHG features in MirGeneDB human miRNA precursors.<br> The files “in_vivo_highly_expressed_miRNA_precursor_IDs.txt” and “in_vivo_lowly_expressed_miRNA_precursor_IDs.txt” show the identity of miRNA precursors that were used to generate the plot of “in vivo expression” in the panel “miRNA processing efficiency” of Figure 6E.<br> The files “Chromatin_pri-miRNA_highly_processed_miRNA_precursor_IDs.txt” and “Chromatin_pri-miRNA_lowly_processed_miRNA_precursor_IDs.txt” show the identity of miRNA precursors that were used to generate the plot of “Chromatin pri-miRNA” in the panel “miRNA processing efficiency” of Figure 6E.
DOI: 10.5281/zenodo.14610432
title: Évaluation de l'état des terres affectées par la désertification en France métropolitaine

description: Ces données ont été produites dans le cadre de l'étude de l'état des terres affectées par la désertification en France métropolitaine, réalisée en 2024 par Nitidae et Data Terra à la demande du Comité Scientifique Français de la Désertification (CSFD).  La méthodologie s'appuie sur les cadres méthodologiques de la Convention des Nations unies sur la lutte contre la désertification (CNULCD), sur les données récentes de la littérature et les données spatiales accessibles et pertinentes.

Ce jeu de données comprend 4 produits: - Indice_aridite_1993_to_2022 : Indice d'aridité calculé sur la période 1993 - 2022 à partir des données mensuelles Météo-France de précipitation et d'évapotranspiration potentielle, selon la méthode de Penman-Monteith.- mann_kendall_tau_avec_pval_onf_005_1993_to_2022 : Évolution (augmentation ou diminution) de l'indice d'aridité sur la période 1993 - 2022, évaluée à partir du calcul du Tau de Mann Kendall (seules les valeurs significatives ont été gardées). - Degradation_indicator_15_3_1_2008_2022 : Dégradation des terres calculées pour la période 2008 - 2022 à partir de la méthodologie de l'UNCCD (Indicateur 15.3.1) basée sur 3 sous-indicateurs : l'évolution de la productivité de la végétation, les changements d'occupation des terres et l’évolution du carbone organique du sol.- Degradation_UNCCD_ESDAC: Dégradation des terres calculées à partir des 3 sous-indicateurs de l'UNCCD et des indicateurs de dégradation des sols fournis par l'ESDAC/JRC (Panagos et al., 2022).
DOI: 10.17044/scilifelab.15144339.v1
title: GHG feature profiling with multiple definitions

description: This is the Supplemental Data 13 of the MapToCleave study. <br>This dataset is related to Figure 6E. The GHG feature is profiled based on the different definitions that are described in the method section “Identifying the presence of the GHG feature using different definitions”. The file “GHG_feature_MapToCleave.txt” shows the presence of the GHG features in the MapToCleave processed and unprocessed miRNA precursors. The file “GHG_feature_MirGeneDB.txt” shows the presence of the GHG features in MirGeneDB human miRNA precursors.<br> The files “in_vivo_highly_expressed_miRNA_precursor_IDs.txt” and “in_vivo_lowly_expressed_miRNA_precursor_IDs.txt” show the identity of miRNA precursors that were used to generate the plot of “in vivo expression” in the panel “miRNA processing efficiency” of Figure 6E.<br> The files “Chromatin_pri-miRNA_highly_processed_miRNA_precursor_IDs.txt” and “Chromatin_pri-miRNA_lowly_processed_miRNA_precursor_IDs.txt” show the identity of miRNA precursors that were used to generate the plot of “Chromatin pri-miRNA” in the panel “miRNA processing efficiency” of Figure 6E.
DOI: 10.7483/opendata.cms.f0r4.lc2l
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH175_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.bxvv.emuu
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH200_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.d36u.iy2a
title: /TprimeBToTH_TLep_Hbb_LH_MT2600_MH200_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.17044/scilifelab.16438206
title: Docking Results

description: Results for the study "Improved protein docking by predicted interface residues". Archive contains GRAMM roto-translations of Ligands around the original position of the Receptor. Several set of docking models have been produced considering different set of protein interface constraintsto score GRAMM roto-translations. Also, AACE18 scoring function results are included. For every docking model, DockQ score has been calculated comparing with both bound and unbound native structures. Find detailed methods at https://www.biorxiv.org/content/10.1101/2021.08.25.457642v1<br>
DOI: 10.17044/scilifelab.16438206.v1
title: Docking Results

description: Results for the study "Improved protein docking by predicted interface residues". Archive contains GRAMM roto-translations of Ligands around the original position of the Receptor. Several set of docking models have been produced considering different set of protein interface constraintsto score GRAMM roto-translations. Also, AACE18 scoring function results are included. For every docking model, DockQ score has been calculated comparing with both bound and unbound native structures. Find detailed methods at https://www.biorxiv.org/content/10.1101/2021.08.25.457642v1<br>