cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13550267.v2
title: Curated sequence database "Life-OF-Mick" first used in Cornet, Magain et al. Exploring syntenic conservation across genomes for phylogenetic studies of organisms subjected to horizontal gene transfers: a case study with Cyanobacteria.

description: This archive is a database of 272 complete proteomes broadly sampled from the three domains of Life. Used in various projects of the Unit of Eukaryotic Phylogenomics (ULiège, Belgium), it is internally referred to as "Life-OF-Mick".<br>The main file is a FASTA file containing 2,176,699 protein sequences: <b>lifeofmick.fasta.gz</b>.<br><br>These correspond to the full conceptual translations of:- 50 archaeal genomes- 115 bacterial genomes- 107 eukaryotic genomes<br>The lineages (following NCBI Taxonomy as of Sep 2016) of the 272 organisms are given in the file <b>lifeofmick.tsv</b>.<br>Archaeal and bacterial proteomes were sampled from Ensembl Bacteria (release 30), whereas eukaryotic proteomes were hand-picked from various public genome portals (i.e., Ensembl Protists, EuPathDB, JGI, NCBI, pico-PLAZA) and institutional websites. Details of the eukaryotic sources (including download links) are available in the file <b>lifeofmick-euka-src.tsv</b>, while archaeal and bacterial download links are provided in the files <b>lifeofmick-arch-src.tsv</b> and <b>lifeofmick-bact-src.tsv</b>, respectively.<br>Eukaryotic proteomes were completed by organellar sequence data (mitochondrial and plastid genomes) fetched from the NCBI databases. A table of these complementations can be found in the file <b>lifeofmick-euka-org-compl.tsv</b>.<br>Finally, eukaryotic proteomes were dereplicated using CD-HIT and a global identity threshold of 99%.<br>Be careful that the "complete proteomes" of <i>Cryptomonas paramecium</i>, <i>Chroomonas mesostigmatica</i>, <i>Lotharella oceanica</i> and <i>Paulinella chromatophora</i> actually correspond to the "plastid" genomes only.
DOI: 10.6084/m9.figshare.13550267.v1
title: Curated sequence database "Life-OF-Mick" first used in Cornet, Magain et al. Exploring syntenic conservation across genomes for phylogenetic studies of organisms subjected to horizontal gene transfers: a case study with Cyanobacteria.

description: This archive is a database of 272 complete proteomes broadly sampled from the three domains of Life. Used in various projects of the Unit of Eukaryotic Phylogenomics (ULiège, Belgium), it is internally referred to as "Life-OF-Mick".<br>The main file is a FASTA file containing 2,176,699 protein sequences: <b>lifeofmick.fasta.gz</b>.<br><br>These correspond to the full conceptual translations of:- 50 archaeal genomes- 115 bacterial genomes- 107 eukaryotic genomes<br>The lineages (following NCBI Taxonomy as of Sep 2016) of the 272 organisms are given in the file <b>lifeofmick.tsv</b>.<br>Archaeal and bacterial proteomes were sampled from Ensembl Bacteria (release 30), whereas eukaryotic proteomes were hand-picked from various public genome portals (i.e., Ensembl Protists, EuPathDB, JGI, NCBI, pico-PLAZA) and institutional websites. Details of the eukaryotic sources (including download links) are available in the file <b>lifeofmick-euka-src.tsv</b>, while archaeal and bacterial download links are provided in the files <b>lifeofmick-arch-src.tsv</b> and <b>lifeofmick-bact-src.tsv</b>, respectively.<br>Eukaryotic proteomes were completed by organellar sequence data (mitochondrial and plastid genomes) fetched from the NCBI databases. A table of these complementations can be found in the file <b>lifeofmick-euka-org-compl.tsv</b>.<br>Finally, eukaryotic proteomes were dereplicated using CD-HIT and a global identity threshold of 99%.<br>Be careful that the "complete proteomes" of <i>Cryptomonas paramecium</i>, <i>Chroomonas mesostigmatica</i>, <i>Lotharella oceanica</i> and <i>Paulinella chromatophora</i> actually correspond to the "plastid" genomes only.
DOI: 10.5281/zenodo.4430496
title: Developing English Academic Writing Course in UMU Application

description: This is my power point about my self paced learning project for the final test of english material development course on language department of state islamic institute of palangka raya central kalimantan indonesia.
DOI: 10.5281/zenodo.4430495
title: Developing English Academic Writing Course in UMU Application

description: This is my power point about my self paced learning project for the final test of english material development course on language department of state islamic institute of palangka raya central kalimantan indonesia.
DOI: 10.21227/ja5c-ad69
title: Holoscopic 3D Micro-Gesture Database

description: Holoscopic micro-gesture recognition (HoMG) database was recorded using a holoscopic 3D camera, which have 3 conventional gestures from 40 participants under different settings and conditions. The principle of holoscopic 3D (H3D) imaging mimics fly’s eye technique that captures a true 3D optical model of the scene using a microlens array. For the purpose of H3D micro-gesture recognition. HoMG database has two subsets. The video subset has 960 videos and the image subset has 30635 images, while both have three type of microgestures (classes). Each subset has been divided into three partitions: training set, development set and testing set where there is not overlap between them in term of the subjects. The database has been used for Holoscopic Micro-Gesture Recognition Challenge 2018 (HoMGR 2018) that was held at IEEE Face & Gesture 2018 (FG2018) - Xi'an, China, 15-19th May 2018 (https://fg2018.cse.sc.edu/Challenges.html). The database is now publicly available for wider research communities in the research areas of holoscopic 3D image processing, machine learning for gesture recognition and its application in AR and VR.
DOI: 10.21227/bpkm-jz98
title: Holoscopic 3D Micro-Gesture Database

description: Holoscopic micro-gesture recognition (HoMG) database was recorded using a holoscopic 3D camera, which have 3 conventional gestures from 40 participants under different settings and conditions. The principle of holoscopic 3D (H3D) imaging mimics fly’s eye technique that captures a true 3D optical model of the scene using a microlens array. For the purpose of H3D micro-gesture recognition. HoMG database has two subsets. The video subset has 960 videos and the image subset has 30635 images, while both have three type of microgestures (classes). Each subset has been divided into three partitions: training set, development set and testing set where there is not overlap between them in term of the subjects. The database has been used for Holoscopic Micro-Gesture Recognition Challenge 2018 (HoMGR 2018) that was held at IEEE Face & Gesture 2018 (FG2018) - Xi'an, China, 15-19th May 2018 (https://fg2018.cse.sc.edu/Challenges.html). The database is now publicly available for wider research communities in the research areas of holoscopic 3D image processing, machine learning for gesture recognition and its application in AR and VR.
DOI: 10.17632/cknvh2n98h.1
title: Data for: Biomarkers and Re-Os geochronology of solid bitumen in the Beiba Dome, northern Sichuan Basin, China: implications for solid bitumen origin and petroleum system evolution

description: Data of GS and GS-MS, and Re-Os isotopes
DOI: 10.17632/95v5s3smg6.1
title: Data for: Carbon isotope fractionation during methane transport in tight sedimentary rocks

description: Measured data of canister degassing in Fig.8a-c.
DOI: 10.6084/m9.figshare.13551299
title: Statistical comparisons

description: Data files containing variable importance in projection (VIP), correlations, and binary differences for models of conservation ~ variable<br>
DOI: 10.6084/m9.figshare.13551299.v1
title: Statistical comparisons

description: Data files containing variable importance in projection (VIP), correlations, and binary differences for models of conservation ~ variable<br>
DOI: 10.6084/m9.figshare.13551278
title: Protein data

description: Amino acid composition, interactions, and general peptide statistics from PomBase and STRING<br>
DOI: 10.6084/m9.figshare.13551278.v1
title: Protein data

description: Amino acid composition, interactions, and general peptide statistics from PomBase and STRING<br>
DOI: 10.6084/m9.figshare.13551275
title: GO Slim data

description: GO slim data for the Grech gene list, retrieved from the GO Term Mapper (https://go.princeton.edu/cgi-bin/GOTermMapper)<br>
DOI: 10.6084/m9.figshare.13551275.v1
title: GO Slim data

description: GO slim data for the Grech gene list, retrieved from the GO Term Mapper (https://go.princeton.edu/cgi-bin/GOTermMapper)<br>
DOI: 10.6084/m9.figshare.13551272
title: Data from Grech et al 2019

description: Dataset from Grech et al 2019. Some authors are missing from Figshare; please see article for full list of authors.<br>
DOI: 10.6084/m9.figshare.13551272.v1
title: Data from Grech et al 2019

description: Dataset from Grech et al 2019. Some authors are missing from Figshare; please see article for full list of authors.<br>
DOI: 10.5517/ccdc.csd.cc24dv3j
title: CCDC 1978547: Experimental Crystal Structure Determination

description: Related Article: You-Wei Xu, Ling Li, Xiang-Ping Hu|2020|Org.Lett.|22|9534|doi:10.1021/acs.orglett.0c03587
DOI: 10.5517/ccdc.csd.cc25mh1c
title: CCDC 2014722: Experimental Crystal Structure Determination

description: Related Article: Philipp Müscher-Polzin, Christian Näther, Wolfgang Bensch|2020|Cryst.Growth Des.|21|156|doi:10.1021/acs.cgd.0c00973
DOI: 10.5517/ccdc.csd.cc265db4
title: CCDC 2030975: Experimental Crystal Structure Determination

description: Related Article: Kristaps Saršu̅ns, Agris Be̅rziņš, Toms Rekis|2020|Cryst.Growth Des.|20|7997|doi:10.1021/acs.cgd.0c01241
DOI: 10.5517/ccdc.csd.cc265d93
title: CCDC 2030974: Experimental Crystal Structure Determination

description: Related Article: Kristaps Saršu̅ns, Agris Be̅rziņš, Toms Rekis|2020|Cryst.Growth Des.|20|7997|doi:10.1021/acs.cgd.0c01241
DOI: 10.5517/ccdc.csd.cc26b872
title: CCDC 2035653: Experimental Crystal Structure Determination

description: Related Article: Kun-Hao Chen, Yi-Hung Liu, Ching-Wen Chiu|2020|Organometallics|39|4645|doi:10.1021/acs.organomet.0c00671
DOI: 10.5517/ccdc.csd.cc26b883
title: CCDC 2035654: Experimental Crystal Structure Determination

description: Related Article: Kun-Hao Chen, Yi-Hung Liu, Ching-Wen Chiu|2020|Organometallics|39|4645|doi:10.1021/acs.organomet.0c00671
DOI: 10.5517/ccdc.csd.cc26b894
title: CCDC 2035655: Experimental Crystal Structure Determination

description: Related Article: Kun-Hao Chen, Yi-Hung Liu, Ching-Wen Chiu|2020|Organometallics|39|4645|doi:10.1021/acs.organomet.0c00671
DOI: 10.5517/ccdc.csd.cc26b8b5
title: CCDC 2035656: Experimental Crystal Structure Determination

description: Related Article: Kun-Hao Chen, Yi-Hung Liu, Ching-Wen Chiu|2020|Organometallics|39|4645|doi:10.1021/acs.organomet.0c00671
DOI: 10.5517/ccdc.csd.cc26b8c6
title: CCDC 2035657: Experimental Crystal Structure Determination

description: Related Article: Kun-Hao Chen, Yi-Hung Liu, Ching-Wen Chiu|2020|Organometallics|39|4645|doi:10.1021/acs.organomet.0c00671
DOI: 10.5517/ccdc.csd.cc26b8d7
title: CCDC 2035658: Experimental Crystal Structure Determination

description: Related Article: Kun-Hao Chen, Yi-Hung Liu, Ching-Wen Chiu|2020|Organometallics|39|4645|doi:10.1021/acs.organomet.0c00671
DOI: 10.5281/zenodo.4430596
title: Wang+Kent-2021-GRL-data file

description: Folder “Figure2e” contains a subfolder that contains all the raw hysteresis measurements (with heated temperatures in degree Celsius in file names) and an Excel spreadsheet that summarizes the hysteresis parameters, which are used in plotting the Day diagram as shown in Figure 2e. Folder “Figure2f-s” contains raw FORC data of specimens GA79.5y and GA84.6y measured after each heating treatment (with heated temperatures in degree Celsius in file names) that are used in plotting the FORC diagrams as shown in Figure 2f to 2s.
DOI: 10.5281/zenodo.4430595
title: Wang+Kent-2021-GRL-data file

description: Folder “Figure2e” contains a subfolder that contains all the raw hysteresis measurements (with heated temperatures in degree Celsius in file names) and an Excel spreadsheet that summarizes the hysteresis parameters, which are used in plotting the Day diagram as shown in Figure 2e. Folder “Figure2f-s” contains raw FORC data of specimens GA79.5y and GA84.6y measured after each heating treatment (with heated temperatures in degree Celsius in file names) that are used in plotting the FORC diagrams as shown in Figure 2f to 2s.
DOI: 10.5281/zenodo.4430615
title: Dades d'immobles en lloguer a la ciutat de Barcelona al web Fotocasa.es al desembre del 2020

description: <strong>El dataset generat recull dades dels pisos que es lloguen a la ciutat de Barcelona a una data determinada, extretes de la web de fotocasa.es. A hores d’ara, webs com Fotocasa ofereixen visualització de dades obertes, però es centren bàsicament en mostrar els preus mitjans dels lloguers de cada comunitat, província, districte o barri de l’Estat Espanyol. </strong> <strong>Per tal d’accedir a un conjunt de dades més ric, on podem trobar diverses característiques de cada lloguer més enllà del preu i localització, hem portat a terme un procés de scraping a la web de Fotocasa. Posteriorment, hem inclòs les dades de preus mitjans de lloguers per barris oferts per l’Agència de l’Habitatge de la Generalitat de Catalunya a cada ítem del dataset. Això ens permetrà contrastar els preus dels lloguers a Fotocasa amb una altra font d’informació de preus, en aquest cas provinent de l’administració pública.</strong>
description: El conjunt de dades extret correspon als pisos que es lloguen a la ciutat de Barcelona al mes de desembre de 2020 a la web fotocasa.es. Per cada lloguer, s'indica també el preu mitjà del barri segons els preus mitjans de lloguers per barris i districtes de la ciutat de Barcelona que posa a disposició l'Agència de l'Habitatge de la Generalitat de Catalunya a la seva web. Tot plegat ens permet comparar el preu ofertat a Fotocasa contra els preus mitjans dels que disposa l'administració pública, a més d'altres característiques de la oferta de lloguer.
DOI: 10.5281/zenodo.4430614
title: Dades d'immobles en lloguer a la ciutat de Barcelona al web Fotocasa.es al desembre del 2020

description: <strong>El dataset generat recull dades dels pisos que es lloguen a la ciutat de Barcelona a una data determinada, extretes de la web de fotocasa.es. A hores d’ara, webs com Fotocasa ofereixen visualització de dades obertes, però es centren bàsicament en mostrar els preus mitjans dels lloguers de cada comunitat, província, districte o barri de l’Estat Espanyol. </strong> <strong>Per tal d’accedir a un conjunt de dades més ric, on podem trobar diverses característiques de cada lloguer més enllà del preu i localització, hem portat a terme un procés de scraping a la web de Fotocasa. Posteriorment, hem inclòs les dades de preus mitjans de lloguers per barris oferts per l’Agència de l’Habitatge de la Generalitat de Catalunya a cada ítem del dataset. Això ens permetrà contrastar els preus dels lloguers a Fotocasa amb una altra font d’informació de preus, en aquest cas provinent de l’administració pública.</strong>
description: El conjunt de dades extret correspon als pisos que es lloguen a la ciutat de Barcelona al mes de desembre de 2020 a la web fotocasa.es. Per cada lloguer, s'indica també el preu mitjà del barri segons els preus mitjans de lloguers per barris i districtes de la ciutat de Barcelona que posa a disposició l'Agència de l'Habitatge de la Generalitat de Catalunya a la seva web. Tot plegat ens permet comparar el preu ofertat a Fotocasa contra els preus mitjans dels que disposa l'administració pública, a més d'altres característiques de la oferta de lloguer.
DOI: 10.34740/kaggle/dsv/1833532
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.4430040
title: Machine learning reactive mixing dataset-18

description: Reactive-mixing dataset-5.1 for machine learning analyses
description: For DIB article
DOI: 10.5281/zenodo.4430039
title: Machine learning reactive mixing dataset-18

description: Reactive-mixing dataset-5.1 for machine learning analyses
description: For DIB article
DOI: 10.6084/m9.figshare.13507197.v4
title: LifehistoryDataHouseMice

description: This is the dataset for Gerber et al. 2021. Population Density and Temperature Influence the Return on MaternalInvestment in Wild House Mice. Frontiers in Ecology and Evolution.
DOI: 10.6084/m9.figshare.13507197.v5
title: LifehistoryDataHouseMice

description: This is the dataset for Gerber et al. 2021. Population Density and Temperature Influence the Return on MaternalInvestment in Wild House Mice. Frontiers in Ecology and Evolution.
DOI: 10.18112/openneuro.ds002422.v1.0.2
title: fMRI: resting state and arithmetic task
DOI: 10.5281/zenodo.4430686
title: Non-parametric reconstruction of the cosmological jerk parameter

description: This .zip file contains a compilation of the jerk parameter data set generated on performing the non-parametric reconstruction, using the Gaussian Process method. The details can be found in the README file.
DOI: 10.5281/zenodo.4430697
title: Non-parametric reconstruction of the cosmological jerk parameter

description: This .zip file contains a compilation of the jerk parameter data set generated on performing the non-parametric reconstruction, using the Gaussian Process method. The details can be found in the README file.
DOI: 10.5281/zenodo.4430685
title: Non-parametric reconstruction of the cosmological jerk parameter

description: This .zip file contains a compilation of the jerk parameter data set generated on performing the non-parametric reconstruction, using the Gaussian Process method. The details can be found in the README file.
DOI: 10.5281/zenodo.4430042
title: Machine learning reactive mixing dataset-19

description: Reactive-mixing dataset-5.2 for machine learning analyses
description: For DIB article
DOI: 10.5281/zenodo.4430041
title: Machine learning reactive mixing dataset-19

description: Reactive-mixing dataset-5.2 for machine learning analyses
description: For DIB article
DOI: 10.6084/m9.figshare.13270796
title: Global Dissolved Vanadium Data

description: This dataset includes observational and modeled dissolved vanadium concentrations in the ocean.<br>
DOI: 10.6084/m9.figshare.13270796.v2
title: Global Dissolved Vanadium Data

description: This dataset includes observational and modeled dissolved vanadium concentrations in the ocean.<br>
DOI: 10.6084/m9.figshare.13270796.v1
title: Global Dissolved Vanadium Data

description: This dataset includes observational and modeled dissolved vanadium concentrations in the ocean.<br>
DOI: 10.6084/m9.figshare.13404410
title: Global Dissolved Nickel Data

description: This dataset includes observational and modeled dissolved nickel concentrations in the ocean.<br>
DOI: 10.6084/m9.figshare.13404410.v3
title: Global Dissolved Nickel Data

description: This dataset includes observational and modeled dissolved nickel concentrations in the ocean.<br>
DOI: 10.6084/m9.figshare.13404410.v2
title: Global Dissolved Nickel Data

description: This dataset includes observational and modeled dissolved nickel concentrations in the ocean.<br>
DOI: 10.6084/m9.figshare.13551437.v1
title: biographies.RData

description: This dataset contains 832 biographies biographies of literature writers retrieved from the Spanish Wikipedia. There is a total of 416 biographies of women writers extracted from the category entitled “Escritoras de España” (https://es.wikipedia.org/wiki/Categoría:Escritoras_de_España) and 416 biographies of male writers extracted from the category “Escritores de España del siglo XX” (https://es.wikipedia.org/wiki/Categoría:Escritores_de_España_del_siglo_XX)
DOI: 10.6084/m9.figshare.13298168
title: JS.csv

description: Job satisfaction scale<br>
DOI: 10.6084/m9.figshare.13298165
title: MOWDOC.csv

description: Dataset for Taking the Measure of Work<br>
DOI: 10.6084/m9.figshare.13298165.v1
title: MOWDOC.csv

description: Dataset for Taking the Measure of Work<br>
DOI: 10.5519/qd.l2v9mk3v
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4699480 records)
DOI: 10.5281/zenodo.4430716
title: Machine learning reactive mixing dataset-20

description: Reactive-mixing dataset-6 for machine learning analyses
description: For DIB article
DOI: 10.5281/zenodo.4430715
title: Machine learning reactive mixing dataset-20

description: Reactive-mixing dataset-6 for machine learning analyses
description: For DIB article
DOI: 10.6084/m9.figshare.13551521
title: Dataset - Experiential Learning Manuscript

description: This dataset was used to report the finds for the manuscript, <i>How Experiential Learning Extends Student’s Knowledge, Skills, and Abilities as Future Communication Professionals.</i>
DOI: 10.6084/m9.figshare.13551521.v1
title: Dataset - Experiential Learning Manuscript

description: This dataset was used to report the finds for the manuscript, <i>How Experiential Learning Extends Student’s Knowledge, Skills, and Abilities as Future Communication Professionals.</i>
DOI: 10.5281/zenodo.4430881
title: ENGLISH-AKUAPEM TWI PARALLEL CORPUS

description: This dataset <em><strong>(verified_data.csv)</strong></em> is bilingual machine translation training corpus for English and Akuapem Twi of 25,421 sentence pairs. <br> A transformer-based machine translator was used to generate initial translations in Akuapem Twi, which were later verified and corrected where necessary by native speakers. <br> The main idea of a typical use case for the dataset is for further training of machine translation models in Akuapem Twi.<br> The data can also be used for other downstream NLP tasks such as Named Entity Recognition and POS tagging, with appropriate additional annotations. <br> Another potential application is training unsupervised embeddings for the Akuapem Twi language.<br> In addition a higher quality 697 crowdsourced sentences <em><strong>(crowdsourced_data.csv) </strong></em>are provided for use as an evaluation set for the tasks highlighted above. It is recommended as a testing dataset for machine translation English to Twi and Twi to English models. <strong>Acknowledgement</strong>: This project was supported by the AI4D language dataset fellowship through K4all and Zindi Africa
DOI: 10.5281/zenodo.4430872
title: OWWC assemblies 2

description: De novo assemblies of Ae. tauschii accessions sequenced in OWWC (http://www.openwildwheat.org/).
DOI: 10.5281/zenodo.4430871
title: OWWC assemblies 2

description: De novo assemblies of Ae. tauschii accessions sequenced in OWWC (http://www.openwildwheat.org/).
DOI: 10.34740/kaggle/dsv/1834071
title: US counties COVID 19 dataset
DOI: 10.5281/zenodo.4308926
title: FT50 Grenser (3) 6-key fagottino: measurements, photos, endoscopic video

description: Dataset of FT50 Grenser (3) 6-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video. A CT-3D scan of this instrument exists. Instrument data and photo material provided by Dr. Tom Lerch, Leiter der Restaurierung-<br> Musikinstrumenten-Museum, Staatliches Institut für Musikforschung PK, Berlin.
DOI: 10.5281/zenodo.4308925
title: FT50 Grenser (3) 6-key fagottino: measurements, photos, endoscopic video

description: Dataset of FT50 Grenser (3) 6-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video. A CT-3D scan of this instrument exists. Instrument data and photo material provided by Dr. Tom Lerch, Leiter der Restaurierung-<br> Musikinstrumenten-Museum, Staatliches Institut für Musikforschung PK, Berlin.
DOI: 10.5281/zenodo.4430893
title: HPA Cell Image Segmentation Dataset

description: This dataset includes annotated cell images obtained from the Human Protein Atlas (http://www.proteinatlas.org), each image contains 4 channels (Microtubules, ER, Nuclei and Protein of Interest), the cells in each image are annotated with polygons and saved into GeoJSON format produced with Kaibu(https://kaibu.org) annotation tool. This dataset is available as an example dataset for running a deep learning-based interactive annotation tools in ImJoy (https://github.com/imjoy-team/imjoy-interactive-segmentation).