cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2gh9t3
title: CCDC 2278835: Experimental Crystal Structure Determination

description: Related Article: Vakhid A. Mamedov, Liliya V. Mustakimova, Zheng-Wang Qu, Hui Zhu, Victor V. Syakaev, Venera R. Galimullina, Leisan R. Shamsutdinova, Il’dar Kh. Rizvanov, Aidar T. Gubaidullin, Oleg G. Sinyashin, Stefan Grimme|2023|J.Org.Chem.|88|16864|doi:10.1021/acs.joc.3c01626
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.cc2gh9v4
title: CCDC 2278836: Experimental Crystal Structure Determination

description: Related Article: Vakhid A. Mamedov, Liliya V. Mustakimova, Zheng-Wang Qu, Hui Zhu, Victor V. Syakaev, Venera R. Galimullina, Leisan R. Shamsutdinova, Il’dar Kh. Rizvanov, Aidar T. Gubaidullin, Oleg G. Sinyashin, Stefan Grimme|2023|J.Org.Chem.|88|16864|doi:10.1021/acs.joc.3c01626
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.cc2gzr07
title: CCDC 2293659: Experimental Crystal Structure Determination

description: Related Article: J. Nepomuk Korber, Christian Wille, Markus Leutzsch, Alois Fürstner|2023|J.Am.Chem.Soc.|145|26993|doi:10.1021/jacs.3c10430
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.cc2gzr18
title: CCDC 2293660: Experimental Crystal Structure Determination

description: Related Article: J. Nepomuk Korber, Christian Wille, Markus Leutzsch, Alois Fürstner|2023|J.Am.Chem.Soc.|145|26993|doi:10.1021/jacs.3c10430
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.cc2gzr29
title: CCDC 2293661: Experimental Crystal Structure Determination

description: Related Article: J. Nepomuk Korber, Christian Wille, Markus Leutzsch, Alois Fürstner|2023|J.Am.Chem.Soc.|145|26993|doi:10.1021/jacs.3c10430
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.cc2gzr3b
title: CCDC 2293662: Experimental Crystal Structure Determination

description: Related Article: J. Nepomuk Korber, Christian Wille, Markus Leutzsch, Alois Fürstner|2023|J.Am.Chem.Soc.|145|26993|doi:10.1021/jacs.3c10430
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.cc2gzr4c
title: CCDC 2293663: Experimental Crystal Structure Determination

description: Related Article: J. Nepomuk Korber, Christian Wille, Markus Leutzsch, Alois Fürstner|2023|J.Am.Chem.Soc.|145|26993|doi:10.1021/jacs.3c10430
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.cc2gzr5d
title: CCDC 2293664: Experimental Crystal Structure Determination

description: Related Article: J. Nepomuk Korber, Christian Wille, Markus Leutzsch, Alois Fürstner|2023|J.Am.Chem.Soc.|145|26993|doi:10.1021/jacs.3c10430
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.cc2h1gvw
title: CCDC 2295328: Experimental Crystal Structure Determination

description: Related Article: Yitong Wang, Zhongyu Liu, Abhrojyoti Mazumder, Christopher G. Gianopoulos, Kristin Kirschbaum, Linda A. Peteanu, Rongchao Jin|2023|J.Am.Chem.Soc.|145|26328|doi:10.1021/jacs.3c09846
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: 10.5281/zenodo.10425960
title: Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine

description: Supplementary Table Captions:

Supplementary Table S9. Evaluation and parameter determination of host and microbiome RNA read classification using simulation datasets

Supplementary Table S10. 40 pathways significantly upregulated in the cecum as compared to the transverse colon

Supplementary Table S11. Host-microbiome gene co-expression network edges

Supplementary Table S12. Host-host gene co-expression network edges

Supplementary Table S13. Microbiome-microbiome gene co-expression network edges

Supplementary Table S14. List of genes included in each gene module identified from the gene co-expression network

Supplementary Table S15. Results of enrichment analysis for each gene module identified from the gene co-expression network

Supplementary Table S16. The top 32 bacterial species in terms of expression abundance based on metatranscriptome profiles

Supplementary Table S17. Number of microbiome RNA reads annotated by the KEGG database

Supplementary Table S18. Results of enrichment analysis of gene modules for each parameter

Supplementary Table S19. Evaluation of modules in each parameter of Newman algorithm

Supplementary Table S20. Evaluation of modules in each parameter of Louvain algorithm

Supplementary Table S21. Evaluation of modules in each parameter of Leiden algorithm

Supplementary Table S22. Evaluation of modules in each parameter of WGCNA
DOI: 10.5281/zenodo.8264875
title: Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine

description: Supplementary Table Captions:

Supplementary Table S9. Evaluation and parameter determination of host and microbiome RNA read classification using simulation datasets

Supplementary Table S10. 40 pathways significantly upregulated in the cecum as compared to the transverse colon

Supplementary Table S11. Host-microbiome gene co-expression network edges

Supplementary Table S12. Host-host gene co-expression network edges

Supplementary Table S13. Microbiome-microbiome gene co-expression network edges

Supplementary Table S14. List of genes included in each gene module identified from the gene co-expression network

Supplementary Table S15. Results of enrichment analysis for each gene module identified from the gene co-expression network

Supplementary Table S16. The top 32 bacterial species in terms of expression abundance based on metatranscriptome profiles

Supplementary Table S17. Number of microbiome RNA reads annotated by the KEGG database

Supplementary Table S18. Results of enrichment analysis of gene modules for each parameter

Supplementary Table S19. Evaluation of modules in each parameter of Newman algorithm

Supplementary Table S20. Evaluation of modules in each parameter of Louvain algorithm

Supplementary Table S21. Evaluation of modules in each parameter of Leiden algorithm

Supplementary Table S22. Evaluation of modules in each parameter of WGCNA
DOI: 10.5281/zenodo.8264876
title: Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine

description: Supplementary Table Captions: Supplementary Table S7. Evaluation and parameter determination of host and microbiome RNA read classification using simulation datasets Supplementary Table S8. 40 pathways significantly upregulated in the cecum as compared to the transverse colon Supplementary Table S9. List of genes included in each gene module identified from the gene co-expression network Supplementary Table S10. Results of enrichment analysis for each gene module identified from the gene co-expression network Supplementary Table S11. Number of microbiome RNA reads annotated by the KEGG database Supplementary Table S12. Results of enrichment analysis of gene modules for each parameter Supplementary Table S13. The top 32 bacterial species in terms of expression abundance based on metatranscriptome profiles
DOI: 10.5281/zenodo.10426033
title: Synthetic phenopacket data from HPOA from 2023-12-22 using phenotype2phenopacket

description: Generated from phenotype2phenopacket commit 37f45b6 on or around Dec 22, 2023 like so:

git clone https://github.com/yaseminbridges/phenotype2phenopacket.git

git checkout 37f45b6

wget http://purl.obolibrary.org/obo/hp/hpoa/phenotype.hpoa

poetry install 







p2p create --phenotype-annotation ./phenotype.hpoa --output-dir test_ppk
DOI: 10.5281/zenodo.10426034
title: Synthetic phenopacket data from HPOA from 2023-12-22 using phenotype2phenopacket

description: Generated from phenotype2phenopacket commit 37f45b6 on or around Dec 22, 2023 like so:

git clone https://github.com/yaseminbridges/phenotype2phenopacket.git

git checkout 37f45b6

wget http://purl.obolibrary.org/obo/hp/hpoa/phenotype.hpoa

poetry install 







p2p create --phenotype-annotation ./phenotype.hpoa --output-dir test_ppk
DOI: 10.15784/601757
title: Ring shear bed deformation measurements

description: This dataset contains AMS results and microstructure analysis from different depths within the sheared till.
DOI: 10.15784/601756
title: Frozen fringe friction

description: This dataset comes from a ring shear device and is a series of values measured from the device including shear resistance as the fringe is growing
DOI: 10.5281/zenodo.10425465
title: Data accompanying:"Isthmus progenitor cells contribute to homeostatic cellular turnover and support regeneration following intestinal injury"

description: Data accompanying some analysis from the manuscript: Isthmus progenitor cells contribute to homeostatic cellular turnover and support regeneration following intestinal injury by Malagola et al.

The full manuscript is available at: https://www.biorxiv.org/content/10.1101/2022.04.26.489611v2 

The following tar.gz files are included in this repo:



original.tar.gz: includes .h5ad files storing (pre-filtered) scRNA-seq data for samples TE001, TE002, TE005, TE006, TE013

TE001.tar.gz: includes UMI counts and protein activity data (.h5ad), output Seurat object from gene expression analysis (.rds), velocity output (.loom) and metadata (.csv and .xlsx) for TE001

TE005.tar.gz: includes UMI counts (.h5ad), velocity output (.loom) and metadata (.csv and .xlsx) for TE005

TE006.tar.gz: includes UMI counts (.h5ad), velocity output (.loom) and metadata (.csv and .xlsx) for TE006
DOI: 10.5281/zenodo.10425464
title: Data accompanying:"Isthmus progenitor cells contribute to homeostatic cellular turnover and support regeneration following intestinal injury"

description: Data accompanying some analysis from the manuscript: Isthmus progenitor cells contribute to homeostatic cellular turnover and support regeneration following intestinal injury by Malagola et al.

The full manuscript is available at: https://www.biorxiv.org/content/10.1101/2022.04.26.489611v2 

The following tar.gz files are included in this repo:



original.tar.gz: includes .h5ad files storing (pre-filtered) scRNA-seq data for samples TE001, TE002, TE005, TE006, TE013

TE001.tar.gz: includes UMI counts and protein activity data (.h5ad), output Seurat object from gene expression analysis (.rds), velocity output (.loom) and metadata (.csv and .xlsx) for TE001

TE005.tar.gz: includes UMI counts (.h5ad), velocity output (.loom) and metadata (.csv and .xlsx) for TE005

TE006.tar.gz: includes UMI counts (.h5ad), velocity output (.loom) and metadata (.csv and .xlsx) for TE006
DOI: 10.5281/zenodo.8042879
title: Supplementary Information and Raw Data for 'Low-dose 4D-STEM Tomography for Beam-Sensitive Nanocomposites'

description: Supplementary information containing TEM data and analysis for the article 

"Low-dose 4D-STEM Tomography for Beam-Sensitive Nanocomposites"

Link to paper: https://doi.org/10.1021/acsmaterialslett.3c01042

The archive provides a documentation of the evaluation routine as a .pdf file and two scripts that are needed for evaluations. In addition, 4 folders are present after unzipping the archive, which contain



the raw 4D-STEM datasets,

vSTEM images,

an example of the denoised vSTEM images,

the denoised and aligned image stack, and the reconstructed volumes.


If there are any questions/bugs, feel free to contact Milena Hugenschmidt (https://orcid.org/0000-0001-5020-9302).
DOI: 10.5281/zenodo.8042880
title: Supplementary Information and Raw Data for 'Low-dose 4D-STEM Tomography for Beam-Sensitive Nanocomposites'

description: Supplementary information containing TEM data and analysis for the article 

"Low-dose 4D-STEM Tomography for Beam-Sensitive Nanocomposites"

Link to paper: https://doi.org/10.1021/acsmaterialslett.3c01042

The archive provides a documentation of the evaluation routine as a .pdf file and two scripts that are needed for evaluations. In addition, 4 folders are present after unzipping the archive, which contain



the raw 4D-STEM datasets,

vSTEM images,

an example of the denoised vSTEM images,

the denoised and aligned image stack, and the reconstructed volumes.


If there are any questions/bugs, feel free to contact Milena Hugenschmidt (https://orcid.org/0000-0001-5020-9302).
DOI: 10.5281/zenodo.10425482
title: Influence de l'environnement sur la capacité de l'encre d'un surligneur à faire du FRET.
DOI: 10.5281/zenodo.10425483
title: Influence de l'environnement sur la capacité de l'encre d'un surligneur à faire du FRET.
DOI: 10.21227/y6ah-j205
title: NANCY SNS-JU project "Italian in-lab testbed dataset 1" D6.6

description: This Dataset provides input data for the development of the B-RAN and attacks models for the NANCY framework,to model training and model inference functions. The data collected plays the role of ML algorithm-specific data preparation. The dataset contains time-series, collected transmitting a video content through the Italtel "VTU - video streaming and transcoding application", that can convert audio and video streams from one format to another, at multiple encodings schemes, changing resolution, bitrate, and video parameters. The data collected are related to the observation of some of the resources involved inthe Usage Scenario: “Fronthaul network of fixed topology – Direct Connectivity”. In the Italtel Italian in-lab testbed, a MEC assisted 5G network scenario with a video streaming application for generating traffic is provided. Two different scenarios were set-up, related to downstream and upstream video flows. The variety of collected features ranges from radio front-end metrics to physical server operating system and network function metrics. The dataset consists of  raw network traffic and extracted flow-based data captured in separate files. Each file captured is associated to a 10min video streaming of the “Big Buck Bunny” video. This video was transmitted on two different bands, N3 and N78, with different resolutions, 480p, 720p, 1080p; both in uplink (UL) and in downlink (DL); the type of protocol monitored is “HTTP protocol”; in case of N78 band, data related to the resource usage were also captured, for a total of more that 100 data files. The collected dataset is representative resource-intensive video traffic that has the greatest impact on 5G/B5G network planning and provisioning. The video streaming dataset includes data directly measured while watching the video on the mobile devices and data directly measured while generating downstream video stream traversing the gNB (i.e., downstream scenario), and vice versa (i.e., upstream scenario). In each experiment, we fixed the location of the UE and the gNB.
DOI: 10.5281/zenodo.10368616
title: Parameters used in the case study of the paper entitled "Bridging the gap between regulatory and operational aspects in the context of increasing distributed generation uptake: a scenario-based bi-level optimization approach""
DOI: 10.5281/zenodo.10368617
title: Parameters used in the case study of the paper entitled "Bridging the gap between regulatory and operational aspects in the context of increasing distributed generation uptake: a stochastic bi-level optimization approach""
DOI: 10.5281/zenodo.10426157
title: Parameters used in the case study of the paper entitled "Bridging the gap between regulatory and operational aspects in the context of increasing distributed generation uptake: a scenario-based bi-level optimization approach""
DOI: 10.5281/zenodo.10426166
title: Parameters used in the case study of the paper entitled "Bridging the gap between regulatory and operational aspects in the context of increasing distributed generation uptake: a scenario-based bi-level optimization approach""
DOI: 10.6084/m9.figshare.22581469
title: The utility of the Cognitive Reserve Index questionnaire in chronic traumatic brain injury

description: <b>Objective:</b> This study examined the relationship between cognitive reserve measured with the Cognitive Reserve Index questionnaire (CRIq) and cognitive and functional outcomes in a chronic traumatic brain injury (TBI) cohort compared to a non-TBI cohort. The utility of the CRIq was compared to common proxies of cognitive reserve (premorbid IQ and years of education) in TBI and non-TBI cohorts. <b>Method:</b> Participants were 105 individuals with moderate-severe TBI (10–33 years post injury) and 91 participants without TBI. Cognitive outcome was examined across four cognitive factors; verbal memory, visual ability and memory, executive attention, and episodic memory. Functional outcome was measured using the Glasgow Outcome Scale Extended. The CRIq total score and three subscale scores (education, work, leisure) were examined. <b>Results:</b> In the TBI cohort, associations were identified between two CRIq subscales and cognitive factors (CRIq education and verbal memory; CRIq work and executive attention). There were no associations between CRIq leisure and cognitive outcomes, or between CRIq and functional outcome. Model selection statistics suggested premorbid IQ and years of education provided a better fit than the CRIq for the relationship between cognitive reserve with two cognitive factors and functional outcome, with neither model providing an improved fit for the remaining two cognitive factors. This finding was broadly consistent in the non-TBI cohort. <b>Conclusion:</b> Cognitive reserve contributes significantly to long-term clinical outcomes following moderate-severe TBI. The relationship between cognitive reserve and long-term cognitive and functional outcomes following TBI is best characterised with traditional proxies of cognitive reserve, mainly premorbid IQ, rather than the CRIq.
DOI: 10.6084/m9.figshare.22581469.v1
title: The utility of the Cognitive Reserve Index questionnaire in chronic traumatic brain injury

description: <b>Objective:</b> This study examined the relationship between cognitive reserve measured with the Cognitive Reserve Index questionnaire (CRIq) and cognitive and functional outcomes in a chronic traumatic brain injury (TBI) cohort compared to a non-TBI cohort. The utility of the CRIq was compared to common proxies of cognitive reserve (premorbid IQ and years of education) in TBI and non-TBI cohorts. <b>Method:</b> Participants were 105 individuals with moderate-severe TBI (10–33 years post injury) and 91 participants without TBI. Cognitive outcome was examined across four cognitive factors; verbal memory, visual ability and memory, executive attention, and episodic memory. Functional outcome was measured using the Glasgow Outcome Scale Extended. The CRIq total score and three subscale scores (education, work, leisure) were examined. <b>Results:</b> In the TBI cohort, associations were identified between two CRIq subscales and cognitive factors (CRIq education and verbal memory; CRIq work and executive attention). There were no associations between CRIq leisure and cognitive outcomes, or between CRIq and functional outcome. Model selection statistics suggested premorbid IQ and years of education provided a better fit than the CRIq for the relationship between cognitive reserve with two cognitive factors and functional outcome, with neither model providing an improved fit for the remaining two cognitive factors. This finding was broadly consistent in the non-TBI cohort. <b>Conclusion:</b> Cognitive reserve contributes significantly to long-term clinical outcomes following moderate-severe TBI. The relationship between cognitive reserve and long-term cognitive and functional outcomes following TBI is best characterised with traditional proxies of cognitive reserve, mainly premorbid IQ, rather than the CRIq.
DOI: 10.5517/ccdc.csd.cc2h22rf
title: CCDC 2295914: Experimental Crystal Structure Determination

description: Related Article: Yuanfeng Li, Difei Zhang, Zhenqiang Huang, Tianyang Zhang, Nan Zheng, Feng Peng, Lei Ying, Fei Huang|2023|J.Mater.Chem.C|11|15426|doi:10.1039/D3TC01742G
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.cc2h2tq4
title: CCDC 2296626: Experimental Crystal Structure Determination

description: Related Article: Haiyan Zou, Ziqian Wang, Dianjun Guo, Lijun Zhang, Shaowu Wang, Xiancui Zhu|2023|Dalton Trans.|53|267|doi:10.1039/D3DT03374K
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.