cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25625/zfpsyj
title: Digital Terrain Models elevation metrics

description: Digital Terrain Models (DTMs), Slope, Aspect, Topographic Position Index (TPI), curvature in profile and plan direction and their average, and flow accumulation derived from airborne LiDAR data acquired over the PTPN 6 estate, Batanghari regency, Harapan rainforest protected area, and Sarolangun regency, in Jambi, Sumatra, Indonesia. Slope, aspect, curvatures, flow accumulation and TPI were calculated following a two-step approach where first the DTM was resampled to 10 m pixel size and then the metrics were calculated and further aggregated to 50 m (see also Jucker et al. 2018 https://doi.org/10.1111/gcb.14415). Original pixel size of DTM: 1m. Geographic Coordinate System: EPSG 32748.
DOI: 10.5517/ccdc.csd.cc28sr3y
title: CCDC 2109150: Experimental Crystal Structure Determination

description: Related Article: Paul Varava, Tak Hin Wong, Zhaowen Dong, Anastasia Yu. Gitlina, Andrzej Sienkiewicz, Wolfram Feuerstein, Rosario Scopelliti, Farzaneh Fadaei-Tirani, Kay Severin|2023|Angew.Chem.,Int.Ed.|62|e202303375|doi:10.1002/anie.202303375
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29fgks
title: CCDC 2128105: Experimental Crystal Structure Determination

description: Related Article: Hao-Wei Chen, Chun-Xiao Jiang, Guang-Lei Ma, Xi-Ying Wu, Wei Jiang, Jiyang Li, Yi Zang, Jia Li, Juan Xiong, Jin-Feng Hu|2023|Phytochemistry|211|113687|doi:10.1016/j.phytochem.2023.113687
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21915543
title: Acoustic emission and rock temperature data of Wetterstein limestone from experimental laboratory tests

description: Data used for paper Influences driving and limiting the Efficacy of Ice Segregation in Alpine Rocks in GRL by Mayer, Eppes, Draebing
DOI: 10.6084/m9.figshare.21915543.v1
title: Acoustic emission and rock temperature data of Wetterstein limestone from experimental laboratory tests

description: Data used for paper Influences driving and limiting the Efficacy of Ice Segregation in Alpine Rocks in GRL by Mayer, Eppes, Draebing
DOI: 10.5281/zenodo.7928556
title: SpliceAI_rocksdb_hg38_chrY

description: SpliceAI RocksDB for chromosome Y of hg38 as used in the AbSplice publication: https://www.nature.com/articles/s41588-023-01373-3 Precomputed SpliceAI scores for all SNVs and indels up to 4 nucleotides are stored in this database. To use this database for fast computation of SpliceAI predictions see: https://github.com/gagneurlab/spliceai_rocksdb This is also implemented in the AbSplice package: https://github.com/gagneurlab/absplice This dataset includes SpliceAI scores. The scores are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc., see the GitHub repository of SpliceAI: https://github.com/Illumina/SpliceAI/tree/master
DOI: 10.5281/zenodo.7928555
title: SpliceAI_rocksdb_hg38_chrY

description: SpliceAI RocksDB for chromosome Y of hg38 as used in the AbSplice publication: https://www.nature.com/articles/s41588-023-01373-3 Precomputed SpliceAI scores for all SNVs and indels up to 4 nucleotides are stored in this database. To use this database for fast computation of SpliceAI predictions see: https://github.com/gagneurlab/spliceai_rocksdb This is also implemented in the AbSplice package: https://github.com/gagneurlab/absplice This dataset includes SpliceAI scores. The scores are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc., see the GitHub repository of SpliceAI: https://github.com/Illumina/SpliceAI/tree/master
DOI: 10.5281/zenodo.7928480
title: SpliceAI_rocksdb_hg38_chr15

description: SpliceAI RocksDB for chromosome 15 of hg38 as used in the AbSplice publication: https://www.nature.com/articles/s41588-023-01373-3 Precomputed SpliceAI scores for all SNVs and indels up to 4 nucleotides are stored in this database. To use this database for fast computation of SpliceAI predictions see: https://github.com/gagneurlab/spliceai_rocksdb This is also implemented in the AbSplice package: https://github.com/gagneurlab/absplice This dataset includes SpliceAI scores. The scores are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc., see the GitHub repository of SpliceAI: https://github.com/Illumina/SpliceAI/tree/master
DOI: 10.5281/zenodo.7928479
title: SpliceAI_rocksdb_hg38_chr15

description: SpliceAI RocksDB for chromosome 15 of hg38 as used in the AbSplice publication: https://www.nature.com/articles/s41588-023-01373-3 Precomputed SpliceAI scores for all SNVs and indels up to 4 nucleotides are stored in this database. To use this database for fast computation of SpliceAI predictions see: https://github.com/gagneurlab/spliceai_rocksdb This is also implemented in the AbSplice package: https://github.com/gagneurlab/absplice This dataset includes SpliceAI scores. The scores are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc., see the GitHub repository of SpliceAI: https://github.com/Illumina/SpliceAI/tree/master
DOI: 10.15129/a391c7e3-25b9-4b30-88f8-7257f01b27bf
title: Data for: "Label-free cytometric evaluation of mitosis via stimulated Raman scattering microscopy and spectral phasor analysis"

description: This data was generated for the publication of a research article of the same title and investigates cytometric changes in a cell model during mitosis using stimulated Raman scattering microscopy and spectral phasor analysis. Spectral and imaging datasets are collated as Excel file format (.csv) or text file format (.txt). SRS images were acquired using a Leica multiphoton microscope. SRS images are provided in .tif file format with post-processing performed using ImageJ. Embargo end date 31/08/23
DOI: 10.4121/a4ad6557-14a4-4c26-b699-a59314472f12
title: Data underlying the MSc thesis: Experimental low frequency mooring analysis of a floating offshore wind turbine

description: Includes 6 DOF motion data, 3 mooring line forces, wind force and wave elevation data for 4 wave gauges. Tests include both monochromatic and bichromatic wave conditions on a moored semi submersible floating wind turbine foundation at scale 1:96. The goal of the research was to excite the natural surge frequencies of a 1:96 NREL semi-submersible model also used during OC5. 2 mooring systems were made to (1) replicate OC5 stiffness and (2) to replicate the surge natural frequency. An electric motor with a magnetic clutch was used to simulate a constant wind force. The experiments were performed in towing tank 2 at the 3Me hydromechanics lab.There are also moored decay tests and wave tests (without the model) available, but these are not processed and to prevent clutter have been excluded. Feel free to send an email if you want the data or if you have any other questions. (youri dot mooc at gmail dot com).
DOI: 10.4121/a4ad6557-14a4-4c26-b699-a59314472f12.v1
title: Data underlying the MSc thesis: Experimental low frequency mooring analysis of a floating offshore wind turbine

description: Includes 6 DOF motion data, 3 mooring line forces, wind force and wave elevation data for 4 wave gauges. Tests include both monochromatic and bichromatic wave conditions on a moored semi submersible floating wind turbine foundation at scale 1:96. The goal of the research was to excite the natural surge frequencies of a 1:96 NREL semi-submersible model also used during OC5. 2 mooring systems were made to (1) replicate OC5 stiffness and (2) to replicate the surge natural frequency. An electric motor with a magnetic clutch was used to simulate a constant wind force. The experiments were performed in towing tank 2 at the 3Me hydromechanics lab.There are also moored decay tests and wave tests (without the model) available, but these are not processed and to prevent clutter have been excluded. Feel free to send an email if you want the data or if you have any other questions. (youri dot mooc at gmail dot com).
DOI: 10.6084/m9.figshare.22891586
title: <strong>Table 4</strong> Relationship of vegetation indices in the tillering phase

description: The research was conducted in 2020–2022 on the territory of the Agricultural Company “Kolos” JSC, located in the Stavropol Territory. The soil of the experimental plot is represented mainly by common chernozem. Studies were conducted to determine the relationship of pigment indices (PSSRAa and PSSRb) in crops of soft winter wheat (variety Grom) and in the models “PSSRAa, PSSRb – VOG1” and “PSSRAa, PSSRb – SIPI” on different agricultural backgrounds in the unstable moisture zone. The study showed that chlorophyll indices (PSSRAa and PSSRb) are high in the seedling phase and markedly high in the tillering phase in all agricultural backgrounds. The models “PSSRAa, PSSRb – VOG1” and “PSSRAa, PSSRb – SIPI” showed high regression dependence of the variables in the seedling phase. Simultaneously, the model “PSSRAa, PSSRb – SIPI” is inversely proportional. During the tillering phase of “PSSRAa, PSSRb – VOG1” and “PSSRAa, PSSRb – SIPI,” the relationship between the variables decreased. However, the correlation in the “PSSRAa, PSSRb – SIPI” model improves, probably due to increased chlorophyll concentration (PSSRb). Consequently, the established relationship of the indices makes it possible to fix the vegetative phase of the development of winter wheat plants and display the state of the cultivated crop.
DOI: 10.6084/m9.figshare.22891586.v1
title: <strong>Table 4</strong> Relationship of vegetation indices in the tillering phase

description: The research was conducted in 2020–2022 on the territory of the Agricultural Company “Kolos” JSC, located in the Stavropol Territory. The soil of the experimental plot is represented mainly by common chernozem. Studies were conducted to determine the relationship of pigment indices (PSSRAa and PSSRb) in crops of soft winter wheat (variety Grom) and in the models “PSSRAa, PSSRb – VOG1” and “PSSRAa, PSSRb – SIPI” on different agricultural backgrounds in the unstable moisture zone. The study showed that chlorophyll indices (PSSRAa and PSSRb) are high in the seedling phase and markedly high in the tillering phase in all agricultural backgrounds. The models “PSSRAa, PSSRb – VOG1” and “PSSRAa, PSSRb – SIPI” showed high regression dependence of the variables in the seedling phase. Simultaneously, the model “PSSRAa, PSSRb – SIPI” is inversely proportional. During the tillering phase of “PSSRAa, PSSRb – VOG1” and “PSSRAa, PSSRb – SIPI,” the relationship between the variables decreased. However, the correlation in the “PSSRAa, PSSRb – SIPI” model improves, probably due to increased chlorophyll concentration (PSSRb). Consequently, the established relationship of the indices makes it possible to fix the vegetative phase of the development of winter wheat plants and display the state of the cultivated crop.
DOI: 10.35003/ipbhge/kbgopx
title: Figure_captions_Community recommendations for geochemical data.docx

description: :unav
DOI: 10.35003/ipbhge/ufb7qg
title: kloecking-et-al_preprint.pdf

description: :unav
DOI: 10.35003/ipbhge/8vumnv
title: Fig_1.jpg

description: :unav
DOI: 10.35003/ipbhge/doo3xm
title: Fig_2.jpg

description: :unav
DOI: 10.35003/ipbhge/vxaqvh
title: Fig_3.jpg

description: :unav
DOI: 10.35003/ipbhge
title: Community recommendations for geochemical data, services and analytical capabilities in the 21st century

description: The majority of geochemical and cosmochemical research is based upon observations and, in particular, upon the acquisition, processing and interpretation of analytical data from physical samples. The exponential increase in volumes and rates of data acquisition over the last century, combined with advances in instruments, analytical methods and an increasing variety of data types analysed, has necessitated the development of new ways of data curation, access and sharing. Together with novel data processing methods, these changes have enabled new scientific insights and are driving innovation in Earth and Planetary Science research. Yet, as approaches to data-intensive research develop and evolve, new challenges emerge. As large and often global data compilations increasingly form the basis for new research studies, institutional and methodological differences in data reporting are proving to be significant hurdles in synthesising data from multiple sources. Consistent data formats and descriptions as well as appropriate information on data quality are becoming crucial to enabling reproducibility and integration of results and fostering confidence for data reuse. Here, we explore the key challenges faced by the geo- and cosmochemistry community and, by drawing comparisons from other communities, recommend possible approaches to overcome them. The first challenge is bringing together the numerous sub-disciplines within our community. One key factor for this convergence will be gaining endorsement from the international geochemical, cosmochemical and analytical societies and associations, journals and institutions. Increased education and outreach, spearheaded by ambassadors recruited from leading scientists across disciplines, will further contribute to raising awareness, and to uniting and mobilising the community. Appropriate incentives, recognition and credit for good data management as well as an improved, user-oriented technical infrastructure will be essential for achieving a cultural change towards an environment in which the effective use and real-time interchange of large datasets is common-place. Finally, the development of best practices for standardised data reporting and exchange, driven by expert working groups, will be a crucial step towards making geo- and cosmochemical data more Findable, Accessible, Interoperable and Reusable by both humans and machines (FAIR).
DOI: 10.18434/mds2-2698
title: Conversion of a piston-cylinder dimensional dataset to the effective area of a mechanical pressure generator
DOI: 10.5281/zenodo.7928478
title: SpliceAI_rocksdb_hg38_chr16

description: SpliceAI RocksDB for chromosome 16 of hg38 as used in the AbSplice publication: https://www.nature.com/articles/s41588-023-01373-3 Precomputed SpliceAI scores for all SNVs and indels up to 4 nucleotides are stored in this database. To use this database for fast computation of SpliceAI predictions see: https://github.com/gagneurlab/spliceai_rocksdb This is also implemented in the AbSplice package: https://github.com/gagneurlab/absplice This dataset includes SpliceAI scores. The scores are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc., see the GitHub repository of SpliceAI: https://github.com/Illumina/SpliceAI/tree/master
DOI: 10.5281/zenodo.7928477
title: SpliceAI_rocksdb_hg38_chr16

description: SpliceAI RocksDB for chromosome 16 of hg38 as used in the AbSplice publication: https://www.nature.com/articles/s41588-023-01373-3 Precomputed SpliceAI scores for all SNVs and indels up to 4 nucleotides are stored in this database. To use this database for fast computation of SpliceAI predictions see: https://github.com/gagneurlab/spliceai_rocksdb This is also implemented in the AbSplice package: https://github.com/gagneurlab/absplice This dataset includes SpliceAI scores. The scores are free for academic and not-for-profit use; other use requires a commercial license from Illumina, Inc., see the GitHub repository of SpliceAI: https://github.com/Illumina/SpliceAI/tree/master
DOI: 10.6084/m9.figshare.22654070.v1
title: Development of a magnetic solid phase extraction method for gemcitabine from rat plasma by using magnetic graphene oxide calix[6]arene composite and its application to pharmacokinetics

description: A highly accurate and precise HPLC-UV method was developed for identification and quantification of gemcitabine anti-cancer drug in rat plasma. A new magnetic graphene oxide-based calixarene composite was developed and used as a solid phase for extraction of gemcitabine from rat plasma. Extraction efficiency has been studied by varying different experimental variables (eluent type, sorbent amount, extraction time and eluent volume etc.) and these were evaluated and optimized. Magnetic solid phase extraction (MSPE) conditions such as amount of solid phase, extraction solvents and their amounts, and adsorption and desorption times were optimized for getting better recoveries. Under the optimized conditions, linearity was evaluated with good correlation coefficient value R<sup>2</sup> (0.9993). Limit of detection (2.0 ng/mL) and limit of quantification (13.0 ng/mL) was assessed using signal-to-noise ratio method. Intraday precision RSD values of gemcitabine (GEM) were found to be less than 4.6% and interday precision values are less than 6.8%. The results obtained during the robustness study were RSD values between 1.2 and 4.6%; these results indicate that the method has effective performance and reliability. The recovery percentages of gemcitabine at three QC level concentrations were obtained in the range from 97.6 to 100.2%.
DOI: 10.6084/m9.figshare.22654070
title: Development of a magnetic solid phase extraction method for gemcitabine from rat plasma by using magnetic graphene oxide calix[6]arene composite and its application to pharmacokinetics

description: A highly accurate and precise HPLC-UV method was developed for identification and quantification of gemcitabine anti-cancer drug in rat plasma. A new magnetic graphene oxide-based calixarene composite was developed and used as a solid phase for extraction of gemcitabine from rat plasma. Extraction efficiency has been studied by varying different experimental variables (eluent type, sorbent amount, extraction time and eluent volume etc.) and these were evaluated and optimized. Magnetic solid phase extraction (MSPE) conditions such as amount of solid phase, extraction solvents and their amounts, and adsorption and desorption times were optimized for getting better recoveries. Under the optimized conditions, linearity was evaluated with good correlation coefficient value R<sup>2</sup> (0.9993). Limit of detection (2.0 ng/mL) and limit of quantification (13.0 ng/mL) was assessed using signal-to-noise ratio method. Intraday precision RSD values of gemcitabine (GEM) were found to be less than 4.6% and interday precision values are less than 6.8%. The results obtained during the robustness study were RSD values between 1.2 and 4.6%; these results indicate that the method has effective performance and reliability. The recovery percentages of gemcitabine at three QC level concentrations were obtained in the range from 97.6 to 100.2%.
DOI: 10.5281/zenodo.6410934
title: Computational validation of clonal and subclonal copy number alterations from bulk tumour sequencing

description: Somatic variant identification from WGS data is a crucial step in the analysis of cancer genomes. Several tools are available to perform mutations calling, however, the noisiness of data requires appropriate quality control assessment. In the preprint work available at https://doi.org/10.1101/2021.02.13.429885 we present CNAqc, an R package devised to assess the quality of allele-specific Copy Number Alterations (CNA), somatic mutations, and tumor purity estimates. In order to test the model, we ran CNAqc on 2778 single-sample PCAWG whole-genomes and 48 TCGA whole-exomes. We uploaded the results of our analysis using the release of the tool available at https://github.com/caravagnalab/CNAqc/releases/tag/rr_22_0.1 in the form of .rds files. All the necessary details for the reproduction of our results are reported in the Supplementary Materials of the above-mentioned manuscript.
DOI: 10.34740/kaggle/dsv/5708372
title: COVID Vaccination in World (updated daily)
DOI: 10.5517/ccdc.csd.cc2bkspd
title: CCDC 2162054: Experimental Crystal Structure Determination

description: Related Article: Mu Chen, Run-Qiang Chen, Yuan Guo, Jian-Xin Chen, Qian Jin, Mei-Hong Chen, Bo-Yong Chen, Zheng-Chao Tu, Wen-Cai Ye, Lei Wang|2023|Phytochemistry|211|113699|doi:10.1016/j.phytochem.2023.113699
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bksxm
title: CCDC 2162061: Experimental Crystal Structure Determination

description: Related Article: Mu Chen, Run-Qiang Chen, Yuan Guo, Jian-Xin Chen, Qian Jin, Mei-Hong Chen, Bo-Yong Chen, Zheng-Chao Tu, Wen-Cai Ye, Lei Wang|2023|Phytochemistry|211|113699|doi:10.1016/j.phytochem.2023.113699
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bksyn
title: CCDC 2162062: Experimental Crystal Structure Determination

description: Related Article: Mu Chen, Run-Qiang Chen, Yuan Guo, Jian-Xin Chen, Qian Jin, Mei-Hong Chen, Bo-Yong Chen, Zheng-Chao Tu, Wen-Cai Ye, Lei Wang|2023|Phytochemistry|211|113699|doi:10.1016/j.phytochem.2023.113699
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cmbq2
title: CCDC 2193334: Experimental Crystal Structure Determination

description: Related Article: Zhi-Wen Liu, Min Song, Jun-Ya Wang, De-Zhi Wang, Biao Sun, Lei Shi, Ren-Wang Jiang, Min Ma, Xiao-Qi Zhang|2023|Phytochemistry|211|113678|doi:10.1016/j.phytochem.2023.113678
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2919xl
title: CCDC 2116429: Experimental Crystal Structure Determination

description: Related Article: Mu Chen, Run-Qiang Chen, Yuan Guo, Jian-Xin Chen, Qian Jin, Mei-Hong Chen, Bo-Yong Chen, Zheng-Chao Tu, Wen-Cai Ye, Lei Wang|2023|Phytochemistry|211|113699|doi:10.1016/j.phytochem.2023.113699
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.