cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2cjnwg
title: CCDC 2190766: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2cjnxh
title: CCDC 2190767: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2cjnyj
title: CCDC 2190768: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2cjnzk
title: CCDC 2190769: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.7141435
title: Enzyme Substrate Classification Dataset for SDRs and SAM-MTases

description: This dataset contains sequence information, three-dimensional structures (from AlphaFold2 model), and substrate classification labels for 358 short-chain dehydrogenase/reductases (SDRs) and 953 S-adenosylmethionine dependent methyltransferases (SAM-MTases). The aminoacid sequences of these enzymes were obtained from the UniProt Knowledgebase (https://www.uniprot.org). The sets of proteins were obtained by querying using InterPro protein family/domain identifiers corresponding to each family: IPR002347 (SDRs) and IPR029063 (SAM-MTases). The query results were filtered by UniProt annotation score, keeping only those with score above 4-out-of-5, and deduplicated by exact sequence matches. The structures were submitted to the publicly available AlphaFold2 protein structure predictor (J. Jumper et al., Nature, 2021, 596, 583) using the ColabFold notebook (https://colab.research.google.com/github/sokrypton/ColabFold/blob/v1.1-premultimer/batch/AlphaFold2_batch.ipynb, M. Mirdita, S. Ovchinnikov, M. Steinegger, Nature Meth., 2022, 19, 679, https://github.com/sokrypton/ColabFold). The model settings used were msa_model = MMSeq2(Uniref+Environmental), num_models = 1, use_amber = False, use_templates = True, do_not_overwrite_results = True. The resulting PDB structures are included as ZIP archives The classification labels were obtained from the substrate and product annotations of the enzyme UniProtKB records. Two approaches were used: substrate clustering based on molecular fingerprints and manual substrate type classification. For the substate clustering, Morgan fingerprints were generated for all enzymatic substrates and products with known structures (excluding cofactors) with radius = 3 using RDKit (https://rdkit.org). The fingerprints were projected onto two-dimensional space using the UMAP algorithm (L. McInnes, J. Healy, 2018, arXiv 1802.03426) and Jaccard metric and clustered using k-means. This procedure generated 9 clusters for SDR substrates and 13 clusters for SAM-MTases. The SMILES representations of the substrates are listed in the SDR_substrates_to_cluster_map_2DIMUMAP.csv and SAM_substrates_to_13clusters_map_2DIMUMAP.csv files. <br> The following manually defined classification tasks are included for SDRs: NADP/NAD cofactor classification; phenol substrate, sterol substrate, coenzyme A (CoA) substrate. For SAM-MTases, the manually defined classification tasks are: biopolymer (protein/RNA/DNA) vs. small molecule substrate, phenol subsrates, sterol substrates, nitrogen heterocycle substrates. The SMARTS strings used to define the substrate classes are listed in substructure_search_SMARTS.docx.<br>
DOI: 10.5281/zenodo.7141434
title: Enzyme Substrate Classification Dataset for SDRs and SAM-MTases

description: This dataset contains sequence information, three-dimensional structures (from AlphaFold2 model), and substrate classification labels for 358 short-chain dehydrogenase/reductases (SDRs) and 953 S-adenosylmethionine dependent methyltransferases (SAM-MTases). The aminoacid sequences of these enzymes were obtained from the UniProt Knowledgebase (https://www.uniprot.org). The sets of proteins were obtained by querying using InterPro protein family/domain identifiers corresponding to each family: IPR002347 (SDRs) and IPR029063 (SAM-MTases). The query results were filtered by UniProt annotation score, keeping only those with score above 4-out-of-5, and deduplicated by exact sequence matches. The structures were submitted to the publicly available AlphaFold2 protein structure predictor (J. Jumper et al., Nature, 2021, 596, 583) using the ColabFold notebook (https://colab.research.google.com/github/sokrypton/ColabFold/blob/v1.1-premultimer/batch/AlphaFold2_batch.ipynb, M. Mirdita, S. Ovchinnikov, M. Steinegger, Nature Meth., 2022, 19, 679, https://github.com/sokrypton/ColabFold). The model settings used were msa_model = MMSeq2(Uniref+Environmental), num_models = 1, use_amber = False, use_templates = True, do_not_overwrite_results = True. The resulting PDB structures are included as ZIP archives The classification labels were obtained from the substrate and product annotations of the enzyme UniProtKB records. Two approaches were used: substrate clustering based on molecular fingerprints and manual substrate type classification. For the substate clustering, Morgan fingerprints were generated for all enzymatic substrates and products with known structures (excluding cofactors) with radius = 3 using RDKit (https://rdkit.org). The fingerprints were projected onto two-dimensional space using the UMAP algorithm (L. McInnes, J. Healy, 2018, arXiv 1802.03426) and Jaccard metric and clustered using k-means. This procedure generated 9 clusters for SDR substrates and 13 clusters for SAM-MTases. The SMILES representations of the substrates are listed in the SDR_substrates_to_cluster_map_2DIMUMAP.csv and SAM_substrates_to_13clusters_map_2DIMUMAP.csv files. <br> The following manually defined classification tasks are included for SDRs: NADP/NAD cofactor classification; phenol substrate, sterol substrate, coenzyme A (CoA) substrate. For SAM-MTases, the manually defined classification tasks are: biopolymer (protein/RNA/DNA) vs. small molecule substrate, phenol subsrates, sterol substrates, nitrogen heterocycle substrates. The SMARTS strings used to define the substrate classes are listed in substructure_search_SMARTS.docx.<br>
DOI: 10.5281/zenodo.7023862
title: A GeoNEX-based 1km hourly land surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) product

description: The dataset is produced by employing a well-established physical-based look-up table (LUT) approach to the GeoNEX gridded top-of-atmosphere bidirectional reflectance factor data acquired by the Advanced Himawari Imager (AHI) and Advanced Baseline Imager (ABI) sensors. It consists of DSR and PAR over both AHI and ABI coverage at an hourly temporal step with a 1km spatial resolution. Full details about the work are under review and can be cited as <strong> </strong><em>Li, R., Wang, D., Wang, W., and Nemani, R.: A GeoNEX-based high spatiotemporal resolution product of land surface downward shortwave radiation and photosynthetically active radiation, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2022-319, in review, 2022.</em> <strong>Due to the file size restrictions, only some sample files are shared here. The full dataset can be accessed through the NASA Advanced Supercomputing Division GeoNEX data portal, using the following URLs: </strong>https://data.nas.nasa.gov/geonex/geonexdata/GOES16/GEONEX-L2/DSR-PAR/ https://data.nas.nasa.gov/geonex/geonexdata/HIMAWARI8/GEONEX-L2/DSR-PAR/
description: It is a gridded product following the convention of the standard GeoNEX products. Each tile contains 600x600 pixels, representing a region of 6° by 6°. Detailed information about the gridding system can be founded at https://www.nasa.gov/geonex/dataproducts. The temporal resolution of the products is every 1 hour. Each file contains three scientific data sets: DSR hourly array, PAR_hourly array, and quality control (QC) array. Users should use the filling value, -9999, to check if DSR/PAR is successfully retrieved or not. The scale factor, 0.1, should be multiplied before use. QC is used to indicate the input source of surface reflectance data. 0: from the MCD43 product; 1: from the climatology data.
DOI: 10.5517/ccdc.csd.cc2cjp0m
title: CCDC 2190770: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2cjp1n
title: CCDC 2190771: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2cjp2p
title: CCDC 2190772: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2cjp3q
title: CCDC 2190773: Experimental Crystal Structure Determination

description: Related Article: Sunil Kumar, Priyasha, Dinabandhu Das|2022|New J.Chem.|46|18465|doi:10.1039/D2NJ03717C
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.cc2ckxlg
title: CCDC 2191966: Experimental Crystal Structure Determination

description: Related Article: Tsukasa Abe, Shinnosuke Horiuchi, Shuichi Hiraoka|2022|Chem.Commun.|58|10829|doi:10.1039/D2CC04496J
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.cc2bwmql
title: CCDC 2171510: Experimental Crystal Structure Determination

description: Related Article: Gürcü Mutlu, Aytuğ Okumuş, Gamze Elmas, Zeynel Kılıç, Remziye Güzel, Büşra Nur Sabah, Leyla Açık, Hatice Mergen, Tuncer Hökelek|2022|New J.Chem.|46|18384|doi:10.1039/D2NJ03001B
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.cc2bsm2v
title: CCDC 2168607: Experimental Crystal Structure Determination

description: Related Article: Felipe Dornelles da Silva, Tanize Bortolotto, Bárbara Tirloni, Natália de Freitas Daudt, Ernesto Schulz Lang, Roberta Cargnelutti|2022|New J.Chem.|46|18165|doi:10.1039/D2NJ02761E
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.cc2bsm3w
title: CCDC 2168608: Experimental Crystal Structure Determination

description: Related Article: Felipe Dornelles da Silva, Tanize Bortolotto, Bárbara Tirloni, Natália de Freitas Daudt, Ernesto Schulz Lang, Roberta Cargnelutti|2022|New J.Chem.|46|18165|doi:10.1039/D2NJ02761E
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.cc2bsm4x
title: CCDC 2168609: Experimental Crystal Structure Determination

description: Related Article: Felipe Dornelles da Silva, Tanize Bortolotto, Bárbara Tirloni, Natália de Freitas Daudt, Ernesto Schulz Lang, Roberta Cargnelutti|2022|New J.Chem.|46|18165|doi:10.1039/D2NJ02761E
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.cc2bsm5y
title: CCDC 2168610: Experimental Crystal Structure Determination

description: Related Article: Felipe Dornelles da Silva, Tanize Bortolotto, Bárbara Tirloni, Natália de Freitas Daudt, Ernesto Schulz Lang, Roberta Cargnelutti|2022|New J.Chem.|46|18165|doi:10.1039/D2NJ02761E
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.cc2bvp63
title: CCDC 2170595: Experimental Crystal Structure Determination

description: Related Article: Krishna Kumar, Anand K. Agrahari, Rajesh Pratap, Vinod K. Tiwari, Subrato Bhattacharya|2022|New J.Chem.|46|18471|doi:10.1039/D2NJ03433F
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: 10.34740/kaggle/dsv/4280535
title: Top 14 Ever Most Viewed YouTube Videos
DOI: 10.6084/m9.figshare.21267924
title: Data and scripts associated with: Benthic composition changes on coral reefs at global scales

description: This data record contains data and scripts associated with the publication: <br> Tebbett SB, Connolly SR, Bellwood DR. Benthic composition changes on coral reefs at global scales. Nature Ecology and Evolution <br> In this study we wanted to gain an insight into likely coral reef configurations of the near future. Specifically we focused on two relatively straightforward questions: 1) how is the benthic composition of coral reefs changing at a global scale? and 2) how, and to what extent, do these changes vary among major marine realms? To explore these questions, we compiled an extensive, global, dataset composed of observations of coral reef benthic composition (cover of 6 benthic categories). <br> The individual datapoints in our dataset were mean site level (i.e. a unique latitude and longitude) benthic community composition data. The six benthic categories were: hard coral, soft corals, macroalgae, low lying algae, sand, and other. We sourced all data from publicly availably databases (all references are supplied in CSV file 1) and previous literature (references and data supplied in CSV files 2 and 3). Specifically, we compiled benthic composition data from six major publicly available monitoring databases: Reef Check, Reef Check Australia, Reef Life Survey, Caribbean Coastal Marine Productivity (CARICOMP), Moorea Coral Reef Long Term Ecological Research and the National Oceanic and Atmospheric Administration (NOAA). The raw data from these six publicly available databases can be accessed through the list of references and relevant accession details listed in CSV file 1. There are 48 references listed in this file as these detail the specific location of each individual data source within these broader databases to ensure raw data can be easily located. To complement the data from these databases and to ensure that our dataset was comprehensive, we then undertook an extensive formal search of the literature for available data. Ultimately, this search process resulted in 83 publications with data that could be used in our study. The references and derived data from these 83 studies are provided in CSV files 2 and 3. <br> This data publication also includes four R scripts (R markdown files) that detail the statistical analyses and compilation of figures from the main text in the manuscript. <br> For full methodological details, please see the published manuscript (outlined above). <br> Further details of the files associated with this data publication can also be found in the 'read me' file.
DOI: 10.6084/m9.figshare.21267369
title: GPS RINEX data from Trignet

description: GPS RINEX data at SCOT station on 13 July 2012. <br> More GPS RINEX data are available from Trignet (http://trignet.co.za/)<br> Data access:<br> The data service is provided through a File Transfer Protocol (FTP) link within the TrigNet website.<br> The Uniform Resource Locator (URL) for this link is ftp://ftp.trignet.co.za.
DOI: 10.6084/m9.figshare.21267369.v1
title: GPS RINEX data from Trignet

description: STEC and GPS RINEX data at SCOT station on 13 July 2012. <br> More GPS RINEX data are available from Trignet (http://trignet.co.za/)<br> Data access:<br> The data service is provided through a File Transfer Protocol (FTP) link within the TrigNet website.<br> The Uniform Resource Locator (URL) for this link is ftp://ftp.trignet.co.za.
DOI: 10.6084/m9.figshare.19172831
title: GToTree HMMs (based on NCBI from initial publication)

description: SCG HMM datasets from the initial publication of GToTree, based on NCBI<br>See: https://github.com/AstrobioMike/GToTree/wiki/SCG-sets
DOI: 10.6084/m9.figshare.19172831.v2
title: GToTree HMMs (based on NCBI from initial publication)

description: SCG HMM datasets from the initial publication of GToTree, based on NCBI<br>See: https://github.com/AstrobioMike/GToTree/wiki/SCG-sets
DOI: 10.48667/mhf1-4b46
title: Data from: Brine driven destruction of clay minerals in Gale crater, Mars

description: This dataset contains files associated with the journal article "Brine Driven Destruction of Clay Minerals in Gale Crater, Mars."

The article presents mineralogical, geochemical, and sedimentological observations made by the Mars Science Laboratory rover, Curiosity, in an area called Glen Torridon, Gale crater, Mars. Rocks exposed in Glen Torridon were deposited in a lake that occupied the floor of Gale crater about 3.5 billion years ago and are stratigraphic and depositional equivalents of rocks exposed ~ 400m away on Vera Rubin ridge. The mineralogy of rocks in these two areas are different despite forming in the same lake at the same time. Glen Torridon rocks contain about 30 wt % clay minerals and 2 wt % or less of the mineral hematite (an iron oxide). In contrast, Vera Rubin ridge rocks contain 5 to 13 wt % clay minerals, with larger quantities (between 9 and 16 wt %) of iron oxide and oxyhydroxide minerals. The observed differences in mineralogy are attributed to preferential post-depositional alteration of Vera Rubin ridge rocks by silica-poor brines. These brines are thought to have formed during the deposition of sedimentary strata of the "sulfate-bearing unit" that overlie Glen Torridon and Vera Rubin ridge rocks. Orbital spacecraft have detected magnesium sulfates in the sulfate-bearing unit. The presence of these highly soluable salts imply that changing climate and/or hydrological conditions in Gale crater resulted in the formation of dense brines during deposition of the sulfate-bearing unit. It is hypothesized that brines infiltrated older clay-bearing sediments, converting iron-rich clay minerals to iron oxides and oxyhydroxides. Glen Torridon rocks also contain a mineral phase not previously identified on the mission. This mineral gives rise to a distinctive x-ray diffraction peak represents a interplanar spacing of 9.22 angstroms. This phase is identified as a mixed-layer serpentine-talc and is thought to have been transported into the crater floor by rivers.

This repository contains:

- Files needed to perform mineral search and Rietveld refinement of measured x-ray diffraction data using BGMN and MDI Jade software.

- Collection times of Alpha Particle X-ray Spectrometer analyses of bulk rock geochemical presented in the article that can be used to retrieve raw data from NASA's Planetary Data system (https://pds-geosciences.wustl.edu/msl/msl-m-apxs-4_5-rdr-v1/mslapx_1xxx/extras/)

- A compilation of Li abundances across Vera Rubin ridge and Glen Torridon measured by the ChemCam that were presented in the article and used as a proxy for rock clay mineral content.

-A link to a software repository containing: 1) a non-commerical, Excel-based program called FULLPAT, used for mineral and x-ray amorphous quantification of x-ray diffraction patterns collected by the CheMin instrument aboard Curiosity. 2) Python code that was used to identify the 9.22 angstrom phase through automated search the American Mineralogist Crystal Structure Database.