cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8283120
title: Shale digital core

description: The data is a digital core model of shale, and the folder contains 400 two-dimensional slices, which can be displayed with three-dimensional visualization software.
DOI: 10.34683/sr238
title: StoneRounds Case: SR238
title: Pattern Dystrophy

description: StoneRounds Case SR238 was diagnosed with Pattern Dystrophy likely caused by mutations in the gene: PRPH2.
DOI: 10.5281/zenodo.8282578
title: Dataset for: Laser absorption spectroscopy measurements of different pulmonary oxygen gas concentrations in transmittance and remittance geometry – phantom study

description: <strong>Significance</strong> GASMAS technique has the potential for continuous, clinical monitoring of pre-term infant lung function, removing the need to X-ray diagnosis and reliance on indirect and relatively slow measurement of blood oxygenation. <strong>Aim</strong> To determine optimal source-detector configuration for reliable path lengths calculation and to estimate the oxygen gas concentration inside the lung cavities filled with humidified gas with four different oxygen gas concentrations ranging between 21% and 100%. <strong>Approach</strong> Anthropomorphic optical phantoms of neonatal thorax with two different geometries were used to acquire Gas in Scattering Media Absorption Spectroscopy (GASMAS) signals, for 30 source-detector configurations in transmittance and remittance geometry of phantoms in two sizes. <strong>Results</strong> The results show that an internal light administration is more likely to provide a high GASMAS signal-to-noise ratio (SNR). In general, better SNRs were obtained with the smaller set of phantoms. The values of path length and O<sub>2</sub> concentrations calculated with signals from the phantoms with optical properties at 820 nm, exhibit higher variations than signals from the phantoms with optical properties at 764 nm. <strong>Conclusion</strong> The study shows that by moving the source and detector over the thorax, most of the lung volumes can potentially be assessed using GASMAS technique.
DOI: 10.5281/zenodo.8282577
title: Dataset for: Laser absorption spectroscopy measurements of different pulmonary oxygen gas concentrations in transmittance and remittance geometry – phantom study

description: <strong>Significance</strong> GASMAS technique has the potential for continuous, clinical monitoring of pre-term infant lung function, removing the need to X-ray diagnosis and reliance on indirect and relatively slow measurement of blood oxygenation. <strong>Aim</strong> To determine optimal source-detector configuration for reliable path lengths calculation and to estimate the oxygen gas concentration inside the lung cavities filled with humidified gas with four different oxygen gas concentrations ranging between 21% and 100%. <strong>Approach</strong> Anthropomorphic optical phantoms of neonatal thorax with two different geometries were used to acquire Gas in Scattering Media Absorption Spectroscopy (GASMAS) signals, for 30 source-detector configurations in transmittance and remittance geometry of phantoms in two sizes. <strong>Results</strong> The results show that an internal light administration is more likely to provide a high GASMAS signal-to-noise ratio (SNR). In general, better SNRs were obtained with the smaller set of phantoms. The values of path length and O<sub>2</sub> concentrations calculated with signals from the phantoms with optical properties at 820 nm, exhibit higher variations than signals from the phantoms with optical properties at 764 nm. <strong>Conclusion</strong> The study shows that by moving the source and detector over the thorax, most of the lung volumes can potentially be assessed using GASMAS technique.
DOI: 10.5281/zenodo.8283049
title: RIXS study of the anomalous magnetic excitations in cuprate/manganite heterostructures: investigating the interplay between charge order, superconductivity and magnetism

description: This is the total dataset for the RIXS experiment performed in DLS corresponding to the beamtime MM22149-1.
DOI: 10.5281/zenodo.8283048
title: RIXS study of the anomalous magnetic excitations in cuprate/manganite heterostructures: investigating the interplay between charge order, superconductivity and magnetism

description: This is the total dataset for the RIXS experiment performed in DLS corresponding to the beamtime MM22149-1.
DOI: 10.4228/zalf-wkny-ys33
title: BIBS Data set: Urban grassland aphid diversity in Berlin, Germany

description: Survey of urban aphid biodiversity carried out in 2017 and partially repeated in 2018 along an urbanization gradient in Berlin, Germany. Surveys took place along diagonal transects in 20 quadrats (4x4m) of dry grasslands from the Cityscapelabs. In 2017, aphid abundances were recorded for aphids on Asteraceae host plants, along with Asteraceae species cover and ant presence. Aphid species present on other type of plant hosts were also noted. In 2018, almost the same subset of quadrats were surveyed, noting only aphid presence on each host plant. This table contains the index of all tables forming this data collection.

Related datasets are listed in the metadata element 'Related Identifier'.
Dataset version 1.0
DOI: 10.5281/zenodo.8283260
title: oral insulin nanoparticle based on PLGA and PEG

description: the project contain: - data sets - Ethical approval - The ARRIVE guidelines 2.0: author checklist - figures 1-3 - Flow chart
DOI: 10.5281/zenodo.8283259
title: oral insulin nanoparticle based on PLGA and PEG

description: the project contain: - data sets - Ethical approval - The ARRIVE guidelines 2.0: author checklist - figures 1-3 - Flow chart
DOI: 10.5281/zenodo.5779237
title: gapseq reconstructions for 5414 genomes from the HRGM collection

description: The data set contains genome-scale metabolic network reconstructions for 5414 microbial genomes from the Human Reference Gut Microbiome (HRGM) collection (doi: 10.1186/s13073-021-00950-7). Reconstructions were made using gapseq (development version 1.1, commit: 564668f). When using the models, please cite: Kim, C.Y., Lee, M., Yang, S. <em>et al.</em> Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. <em>Genome Med</em> <strong>13, </strong>134 (2021). DOI: 10.1186/s13073-021-00950-7 Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. <em>Genome Biol</em> <strong>22, </strong>81 (2021). DOI: 10.1186/s13059-021-02295-1 The models were reconstructed using the following workflow. <pre><code class="language-bash"># Reaction & Pathway prediction ./gapseq find -b 200 -v 1 -p all -k -t &lt;Bacteria|Archaea&gt; &lt;genomeID&gt;.fna.gz # Transporter prediction ./gapseq find-transport -b 200 -k &lt;genomeID&gt;.fna.gz # Draft network reconstruction ./gapseq draft -r &lt;genomeID&gt;-all-Reactions.tbl -t &lt;genomeID&gt;-Transporter.tbl -b &lt;Bacteria|Archaea&gt; -c &lt;genomeID&gt;.fna.gz -p &lt;genomeID&gt;-all-Pathways.tbl -u 200 -l 100 # gapfill/growth medium prediction ./gapseq medium -m &lt;genomeID&gt;-draft.RDS -p &lt;genomeID&gt;-all-Pathways.tbl -c "cpd00007:0" # Gap-filling # (If H2 is part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100 -e highH2 # (If H2 is not part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100</code></pre>
description: {"references": ["Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1", "Kim, C.Y., Lee, M., Yang, S. et al. Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Med 13, 134 (2021). https://doi.org/10.1186/s13073-021-00950-7"]}
DOI: 10.5281/zenodo.7645465
title: gapseq reconstructions for 5414 genomes from the HRGM collection

description: The data set contains genome-scale metabolic network reconstructions for 5414 microbial genomes from the Human Reference Gut Microbiome (HRGM) collection (doi: 10.1186/s13073-021-00950-7). Reconstructions were made using gapseq (development version: 1.2, commit 8c80c5e; Sequence DB md5sum: 1139b8e (2021-06-02, Bacteria). When using the models, please cite: Kim, C.Y., Lee, M., Yang, S. <em>et al.</em> Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. <em>Genome Med</em> <strong>13, </strong>134 (2021). DOI: 10.1186/s13073-021-00950-7 Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. <em>Genome Biol</em> <strong>22, </strong>81 (2021). DOI: 10.1186/s13059-021-02295-1 The models were reconstructed using the following workflow. <pre><code class="language-bash"># Reaction & Pathway prediction ./gapseq find -b 200 -v 1 -p all -k -t &lt;Bacteria|Archaea&gt; &lt;genomeID&gt;.fna.gz # Transporter prediction ./gapseq find-transport -b 200 -k &lt;genomeID&gt;.fna.gz # Draft network reconstruction ./gapseq draft -r &lt;genomeID&gt;-all-Reactions.tbl -t &lt;genomeID&gt;-Transporter.tbl -b &lt;Bacteria|Archaea&gt; -c &lt;genomeID&gt;.fna.gz -p &lt;genomeID&gt;-all-Pathways.tbl -u 200 -l 100 # gapfill/growth medium prediction ./gapseq medium -m &lt;genomeID&gt;-draft.RDS -p &lt;genomeID&gt;-all-Pathways.tbl -c "cpd00007:0" # Gap-filling # (If H2 is part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100 -e highH2 # (If H2 is not part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100</code></pre> Please note that the model collection contains 2 additional genome-scale metabolic for genomes, that are not part of the HRGM collection: NISW_Genome_0001 (Assembly: GCF_007164725.1, Species: <em>Dialister hominis</em>) NISW_Genome_0002 (Assembly: GCF_000296465.1, Species: <em>Barnesiella intestinihominis</em>)
description: {"references": ["Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1", "Kim, C.Y., Lee, M., Yang, S. et al. Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Med 13, 134 (2021). https://doi.org/10.1186/s13073-021-00950-7"]}
DOI: 10.5281/zenodo.8283247
title: gapseq reconstructions for 5414 genomes from the HRGM collection

description: The data set contains genome-scale metabolic network reconstructions for 5414 microbial genomes from the Human Reference Gut Microbiome (HRGM) collection (doi: 10.1186/s13073-021-00950-7). Reconstructions were made using gapseq (development version: 1.2, commit 13d88a68; Sequence DB md5sum: bf8ba98 (2021-06-02, Bacteria). When using the models, please cite: Kim, C.Y., Lee, M., Yang, S. <em>et al.</em> Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. <em>Genome Med</em> <strong>13, </strong>134 (2021). DOI: 10.1186/s13073-021-00950-7 Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. <em>Genome Biol</em> <strong>22, </strong>81 (2021). DOI: 10.1186/s13059-021-02295-1 The models were reconstructed using the following workflow. <pre><code class="language-bash"># Reaction & Pathway prediction ./gapseq find -b 200 -v 1 -p all -k -t &lt;Bacteria|Archaea&gt; &lt;genomeID&gt;.fna.gz # Transporter prediction ./gapseq find-transport -b 200 -k &lt;genomeID&gt;.fna.gz # Draft network reconstruction ./gapseq draft -r &lt;genomeID&gt;-all-Reactions.tbl -t &lt;genomeID&gt;-Transporter.tbl -b &lt;Bacteria|Archaea&gt; -c &lt;genomeID&gt;.fna.gz -p &lt;genomeID&gt;-all-Pathways.tbl -u 200 -l 100 # gapfill/growth medium prediction ./gapseq medium -m &lt;genomeID&gt;-draft.RDS -p &lt;genomeID&gt;-all-Pathways.tbl -c "cpd00007:0" # Gap-filling # (If H2 is part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100 -e highH2 # (If H2 is not part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100</code></pre> Please note that the model collection contains 2 additional genome-scale metabolic for genomes, that are not part of the HRGM collection: NISW_Genome_0001 (Assembly: GCF_007164725.1, Species: <em>Dialister hominis</em>) NISW_Genome_0002 (Assembly: GCF_000296465.1, Species: <em>Barnesiella intestinihominis</em>)
description: {"references": ["Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1", "Kim, C.Y., Lee, M., Yang, S. et al. Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Med 13, 134 (2021). https://doi.org/10.1186/s13073-021-00950-7"]}
DOI: 10.5281/zenodo.5779236
title: gapseq reconstructions for 5414 genomes from the HRGM collection

description: The data set contains genome-scale metabolic network reconstructions for 5414 microbial genomes from the Human Reference Gut Microbiome (HRGM) collection (doi: 10.1186/s13073-021-00950-7). Reconstructions were made using gapseq (development version: 1.2, commit 13d88a68; Sequence DB md5sum: bf8ba98 (2021-06-02, Bacteria). When using the models, please cite: Kim, C.Y., Lee, M., Yang, S. <em>et al.</em> Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. <em>Genome Med</em> <strong>13, </strong>134 (2021). DOI: 10.1186/s13073-021-00950-7 Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. <em>Genome Biol</em> <strong>22, </strong>81 (2021). DOI: 10.1186/s13059-021-02295-1 The models were reconstructed using the following workflow. <pre><code class="language-bash"># Reaction & Pathway prediction ./gapseq find -b 200 -v 1 -p all -k -t &lt;Bacteria|Archaea&gt; &lt;genomeID&gt;.fna.gz # Transporter prediction ./gapseq find-transport -b 200 -k &lt;genomeID&gt;.fna.gz # Draft network reconstruction ./gapseq draft -r &lt;genomeID&gt;-all-Reactions.tbl -t &lt;genomeID&gt;-Transporter.tbl -b &lt;Bacteria|Archaea&gt; -c &lt;genomeID&gt;.fna.gz -p &lt;genomeID&gt;-all-Pathways.tbl -u 200 -l 100 # gapfill/growth medium prediction ./gapseq medium -m &lt;genomeID&gt;-draft.RDS -p &lt;genomeID&gt;-all-Pathways.tbl -c "cpd00007:0" # Gap-filling # (If H2 is part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100 -e highH2 # (If H2 is not part of the medium) ./gapseq fill -m &lt;genomeID&gt;-draft.RDS -n &lt;genomeID&gt;-medium.csv -c &lt;genomeID&gt;-rxnWeights.RDS -g &lt;genomeID&gt;-rxnXgenes.RDS -b 100</code></pre> Please note that the model collection contains 2 additional genome-scale metabolic for genomes, that are not part of the HRGM collection: NISW_Genome_0001 (Assembly: GCF_007164725.1, Species: <em>Dialister hominis</em>) NISW_Genome_0002 (Assembly: GCF_000296465.1, Species: <em>Barnesiella intestinihominis</em>)
description: {"references": ["Zimmermann, J., Kaleta, C. & Waschina, S. gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models. Genome Biol 22, 81 (2021). https://doi.org/10.1186/s13059-021-02295-1", "Kim, C.Y., Lee, M., Yang, S. et al. Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Med 13, 134 (2021). https://doi.org/10.1186/s13073-021-00950-7"]}
DOI: 10.6084/m9.figshare.23950824.v1
title: Supplementary Material for: Krukenberg tumor of gastric origin in pregnant women with preeclampsia

description: Krukenberg tumor refers to a malignancy in the ovary that metastasizes from a primary site, classically the gastrointestinal tract. Pregnancy complicated with a Krukenberg tumor is very rare. In this report, we present two unusual cases of pregnant women with Krukenberg tumors of gastric origin. One case was a full-term pregnant woman with preeclampsia (PE) who underwent a caesarean section when bilateral enlarged ovaries were incidentally identified. Histopathology of the wedge resection biopsy showed single-ring cell carcinoma; this was followed by gastroscopy, which indicated a gastric origin. The woman received chemotherapy but died six months later. Another case was a pregnant woman at 30 gestational weeks with abdominal pain complicated with early-onset PE. Ultrasonography and magnetic resonance imaging showed bilateral enlarged ovaries and elevated tumor markers. Gastroscopy indicated linitis plastica. After an emergency caesarean section, adnexectomy was performed, and postoperative histopathology confirmed a Krukenberg tumor. The woman died two months after delivery. Gastrointestinal symptoms during pregnancy may indicate a malignancy of rare gastrointestinal origin. PE complicated with Krukenberg tumors in pregnancy should be considered in future studies.
DOI: 10.6084/m9.figshare.24033336
title: All code.R

description: The code for <b>Climate risk and higher moments time-frequency connectedness among carbon, energy and metals markets</b><b>.</b>
DOI: 10.5281/zenodo.8280100
title: Data for Adaptor Protein-3 Produces Synaptic Vesicles that Release Phasic Dopamine

description: Raw data for publication titled Adaptor Protein-3 Produces Synaptic Vesicles that Release Phasic Dopamine.
DOI: 10.5281/zenodo.8280101
title: Data for Adaptor Protein-3 Produces Synaptic Vesicles that Release Phasic Dopamine

description: Raw data for publication titled Adaptor Protein-3 Produces Synaptic Vesicles that Release Phasic Dopamine.
DOI: 10.5281/zenodo.8283309
title: SciExpeM - 10.5281/zenodo.8283309

description: Yifan Jin , Xin Li , Xin Wang , Zhihao Ma * , Xianglin Chu
DOI: 10.5281/zenodo.8283308
title: SciExpeM - 10.5281/zenodo.8283309

description: Yifan Jin , Xin Li , Xin Wang , Zhihao Ma * , Xianglin Chu
DOI: 10.5281/zenodo.8283317
title: SciExpeM - 10.5281/zenodo.8283317

description: Yifan Jin , Xin Li , Xin Wang , Zhihao Ma * , Xianglin Chu
DOI: 10.5281/zenodo.8283316
title: SciExpeM - 10.5281/zenodo.8283317

description: Yifan Jin , Xin Li , Xin Wang , Zhihao Ma * , Xianglin Chu
DOI: 10.5517/ccdc.csd.cc2f4grt
title: CCDC 2238626: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc2f4gsv
title: CCDC 2238627: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc2f4gtw
title: CCDC 2238628: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc2f4gvx
title: CCDC 2238629: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc2f4gwy
title: CCDC 2238630: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc2f4gxz
title: CCDC 2238631: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc2f4gy0
title: CCDC 2238632: Experimental Crystal Structure Determination

description: Related Article: Ranran Li, Bin Ma, Shengtao Li, Chongdao Lu, Peng An|2023|Chemical Science|14|8905|doi:10.1039/D3SC02595K
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.cc25x60b
title: CCDC 2023091: Experimental Crystal Structure Determination

description: Related Article: Jiyu Sun, Daniel A. Decato, Vyacheslav S. Bryantsev, Eric A. John, Orion B. Berryman|2023|Chemical Science|14|8924|doi:10.1039/D3SC02348F
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.