cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/5ftq-3m98
title: Beta Lactamase Sequences

description: A well-known publicly available database namely UniProt was the main source for collection beta-lactamase and non-beta-lactamase protein sequences. To obtain relevant positive sequences ‘beta-lactamase’ was used as a keyword. The dataset was meticulously collected by excluding ambiguous sequences, only those sequences were selected which were not annotated with dubious words like potential, by similarity or probable. Moreover, the sequence should be a complete sequence and hence should not be annotated with words like fragment.beta-lactamase protein sequences as well. A total of 2172 sequences of β-lactamases were obtained after selecting representative sequences using CD-HIT. Similarly, non-beta-lactamase sequences were also collected. UniProt database was used to collect a set of 3463 non-beta-lactamase sequences.
DOI: 10.21227/jjwj-py59
title: Beta Lactamase Sequences

description: A well-known publicly available database namely UniProt was the main source for collection beta-lactamase and non-beta-lactamase protein sequences. To obtain relevant positive sequences ‘beta-lactamase’ was used as a keyword. The dataset was meticulously collected by excluding ambiguous sequences, only those sequences were selected which were not annotated with dubious words like potential, by similarity or probable. Moreover, the sequence should be a complete sequence and hence should not be annotated with words like fragment.beta-lactamase protein sequences as well. A total of 2172 sequences of β-lactamases were obtained after selecting representative sequences using CD-HIT. Similarly, non-beta-lactamase sequences were also collected. UniProt database was used to collect a set of 3463 non-beta-lactamase sequences.
DOI: 10.5281/zenodo.3515471
title: Supporting Data for Tanioka and Matsumoto (2019), Biogeosciences (submitted)

description: This dataset contains files used to make figures for Tanioka and Matsumoto (2019), <em>Biogeosciences</em> (submitted). See "README.rtf" for the descriptions.
DOI: 10.5281/zenodo.3515470
title: Supporting Data for Tanioka and Matsumoto (2020), A meta-analysis on environmental drivers of marine phytoplankton C:N:P, Biogeosciences

description: This dataset contains files used to make figures for Tanioka, T., & Matsumoto, K. (2020). A meta-analysis on environmental drivers of marine phytoplankton C:N:P. <em>Biogeosciences</em>, <em>17</em>(11), 2939–2954. https://doi.org/10.5194/bg-17-2939-2020 <strong>Files uploaded:</strong> <strong>Bibliography</strong> AppendixS1.pdf : list of 104 papers used in the main meta-analysis. <strong>Excel spreadsheets</strong>: New_data_190211a.xlsx: C:N and C:P dataset res_all_190211a_P.csv: Effect sizes calculated for each P experiment res_all_190211a_N.csv: Effect sizes calculated for each N experiment res_all_190211a_Fe.csv: Effect sizes calculated for each Fe experiment res_all_190211a_I.csv: Effect sizes calculated for each I experiment res_all_190211a_I.csv: Effect sizes calculated for each T experiment META_BIiblio_articles1st_k4899.xlsx : list of 4899 in the first round of data collection/screening (see Fig. 1 in the main text) META_Biblio_articles2nd_k948.xlsx : list of 948 papers in the second round of data collection/screening (see Fig. 1 in the main text) META_Biblio_articles3rd_k196.xlsx : list of 196 papers in the third round of data collection/screening (see Fig. 1 in the main text) <strong>R scripts:</strong> analysis_190211a_test_P.R: script to conduct meta-analysis on P experiments analysis_190211a_test_N.R: script to conduct meta-analysis on N experiments analysis_190211a_test_F.R: script to conduct meta-analysis on Fe experiments analysis_190211a_test_I.R: script to conduct meta-analysis on I experiments analysis_190211a_test_T.R: script to conduct meta-analysis on T experiments functions_eff_logrr.R: function file to calculate ln(RR) (used in “analysis_190211a_test_X.R”) functions_scalc.R function file to calculate s-factor (used in “analysis_190211a_test_X.R”)
description: This is Version 2 of the C:N:P stoichiometry dataset
DOI: 10.5281/zenodo.3515480
title: HuProt array IgM and IgG signals from rat serum (SHR-A3 and SHR-A3(Stim1 B2)

description: Data obtained by interrogating Hu-Prot arrays (CDI Labs) with serum from SHR-A3 and SHR-A3(Stim1 B2) congenic rats. Detection employed fluorescent antibodies specific for rat IgM or IgG
DOI: 10.5281/zenodo.3515481
title: HuProt array IgM and IgG signals from rat serum (SHR-A3 and SHR-A3(Stim1 B2)

description: Data obtained by interrogating Hu-Prot arrays (CDI Labs) with serum from SHR-A3 and SHR-A3(Stim1 B2) congenic rats. Detection employed fluorescent antibodies specific for rat IgM or IgG
DOI: 10.21227/q295-3655
title: A Machine Learning Benchmark for Facies Classification

description: The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As a result, researchers have often resorted to annotating their own training and testing data. However, different researchers may annotate different classes, or use different train and test splits. In addition, it is common for papers that apply deep learning for facies classification to not contain quantitative results, and rather rely solely on visual inspection of the results. All of these practices have lead to subjective results and have greatly hindered the ability to compare different machine learning models against each other and understand the advantages and disadvantages of each approach.To address these issues, we open-source an accurate 3D geological model of the Netherlands F3 Block. This geological model is based on both well log data and 3D seismic data and is grounded on the careful study of the geology of the region. Furthermore, we propose two baseline models for facies classification based on deconvolution networks and make their codes publicly available. Finally, we propose a scheme for evaluating different models on this dataset, and we share the results of our baseline models. In addition to making the dataset and the code publicly available, this work can help advance research in this area and create an objective benchmark for comparing the results of different machine learning approaches for facies classification for researchers to use in the future.
DOI: 10.21227/scvy-vr77
title: Extreme Video Completion Dataset

description: This data set contains 50 low resolution (640 x 360) short videos containing a variety real life activities.
DOI: 10.21227/yxwe-d468
title: A Machine Learning Benchmark for Facies Classification

description: The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As a result, researchers have often resorted to annotating their own training and testing data. However, different researchers may annotate different classes, or use different train and test splits. In addition, it is common for papers that apply deep learning for facies classification to not contain quantitative results, and rather rely solely on visual inspection of the results. All of these practices have lead to subjective results and have greatly hindered the ability to compare different machine learning models against each other and understand the advantages and disadvantages of each approach.To address these issues, we open-source an accurate 3D geological model of the Netherlands F3 Block. This geological model is based on both well log data and 3D seismic data and is grounded on the careful study of the geology of the region. Furthermore, we propose two baseline models for facies classification based on deconvolution networks and make their codes publicly available. Finally, we propose a scheme for evaluating different models on this dataset, and we share the results of our baseline models. In addition to making the dataset and the code publicly available, this work can help advance research in this area and create an objective benchmark for comparing the results of different machine learning approaches for facies classification for researchers to use in the future.
DOI: 10.15468/cmzket
title: Clarifying the identity of the Uruguayan meadow katydid Conocephalus doryphorus (Orthoptera: Tettigoniidae: Conocephalini)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Greco-Spingola, Silvana, Braun, Holger (2019): Clarifying the identity of the Uruguayan meadow katydid Conocephalus doryphorus (Orthoptera: Tettigoniidae: Conocephalini). Zootaxa 4688 (1): 147-150, DOI: https://doi.org/10.11646/zootaxa.4688.1.10
DOI: 10.7910/dvn/4yhosk/rquvm7
title: 2018 Larkin et al Supplementary Material CCS expert elicitation_risk assessment issues.pdf

description: Supplementary information - CCS expert elicitation re risk assessment
DOI: 10.15468/efaodd
title: Neotype designation and re-description of Prolachlanius resinatus (Hagen) (Neuroptera, Hemerobiidae) from Baltic amber, with the first record of the species from Rovno amber

description: This dataset contains the digitized treatments in Plazi based on the original journal article Makarkin, Vladimir N., Perkovsky, Evgeny E., Gröhn, Carsten (2019): Neotype designation and re-description of Prolachlanius resinatus (Hagen) (Neuroptera, Hemerobiidae) from Baltic amber, with the first record of the species from Rovno amber. Zootaxa 4688 (1): 57-70, DOI: https://doi.org/10.11646/zootaxa.4688.1.2
DOI: 10.5281/zenodo.3515486
title: Database of mechanism of action paths for selected drug-disease indications

description: Mechanistic paths that lead from drug to disease in a heterogeneous network. Version 1.1.0 includes a new tab `metapaths_biolink` where the majority of node and edge types have been mapped to entities and relationship slots in the biolink model. Concepts unable to be mapped at this time are represented in ALL CAPS. JSON version of the paths available on GitHub
DOI: 10.5281/zenodo.3515487
title: Database of mechanism of action paths for selected drug-disease indications

description: Mechanistic paths that lead from drug to disease in a heterogeneous network. JSON version of the paths available on GitHub
DOI: 10.7910/dvn/l4kq76/dxakvi
title: ReplicationDataPublius.tab

description: Dataset as SPSS file
DOI: 10.7910/dvn/l4kq76/fw3ejt
title: ReplicationDataPublius-1.tab

description: Dataset as Excel file
DOI: 10.7910/dvn/l4kq76/rofctp
title: ReplicationSyntaxPublius.sps

description: Syntax to replicate the analysis
DOI: 10.7910/dvn/l4kq76/styku5
title: Codebook.pdf

description: Codebook
DOI: 10.18152/moredata/365
title: KITT+. Datensammlung

description: [MoReData.Quality] Value=50
description: [MoReData.Quality] Nr=77
DOI: 10.7910/dvn/47wsrs/z9buqk
title: Dataset 1.Jeehp_16_30_raw data (BCS-data_R).xlsx

description: :unav
DOI: 10.7910/dvn/eoc6oc/3iefn0
title: Dataset 1. Jeehp_16_29_raw data.tab

description: :unav
DOI: 10.7910/dvn/eoc6oc/gi5cjg
title: Supple 1. Example of a grading rubric used during a peer-assisted learning session.docx

description: :unav
DOI: 10.15468/kusdly
title: First record of two rare spider crabs (Crustacea: Decapoda: Brachyura: Majoidea) from Brazil

description: This dataset contains the digitized treatments in Plazi based on the original journal article Alves-Júnior, Flavio De Almeida, Lucatelli, Débora, Santana, William, Souza-Filho, Jesser Fidelis De (2019): First record of two rare spider crabs (Crustacea: Decapoda: Brachyura: Majoidea) from Brazil. Zootaxa 4688 (1): 111-118, DOI: https://doi.org/10.11646/zootaxa.4688.1.6
DOI: 10.15468/togyfg
title: Confirmation of Trachischium guentheri (Serpentes: Colubridae) from Tibet, China, with description of Tibetan T. monticola

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wang, Kai, Jiang, Ke, Jin, Jieqiong, Liu, Xu, Che, Jing (2019): Confirmation of Trachischium guentheri (Serpentes: Colubridae) from Tibet, China, with description of Tibetan T. monticola. Zootaxa 4688 (1): 101-110, DOI: https://doi.org/10.11646/zootaxa.4688.1.5
DOI: 10.15468/uky1nc
title: Three new species of the free-living marine nematode Metoncholaimus Filipjev 1918 (Enoplida, Oncholaimidae) from Argentinean coasts

description: This dataset contains the digitized treatments in Plazi based on the original journal article Russo, Virginia Lo, Pastor De Ward, Catalina T. (2019): Three new species of the free-living marine nematode Metoncholaimus Filipjev 1918 (Enoplida, Oncholaimidae) from Argentinean coasts. Zootaxa 4688 (1): 86-100, DOI: https://doi.org/10.11646/zootaxa.4688.1.4
DOI: 10.15468/xhwkp6
title: Taxonomic review of the leafhopper genus Grammacephalus Haupt (Hemiptera: Cicadellidae: Deltocephalinae: Scaphoideini) with description of a new species from Pakistan

description: This dataset contains the digitized treatments in Plazi based on the original journal article Shah, Bismillah, Naveed, Hassan, Duan, Yani (2019): Taxonomic review of the leafhopper genus Grammacephalus Haupt (Hemiptera: Cicadellidae: Deltocephalinae: Scaphoideini) with description of a new species from Pakistan. Zootaxa 4688 (1): 71-85, DOI: https://doi.org/10.11646/zootaxa.4688.1.3
DOI: 10.18112/openneuro.ds002249.v1.0.0
title: TODO: name of the dataset
DOI: 10.5281/zenodo.3514885
title: scRNA-seq dataset prefiltered from Paul et al. (2015), Cell

description: Preprocessed dataset from Paul et al. (2015), Cell, to use for tradeSeq vignette.
DOI: 10.5281/zenodo.3515126
title: data set

description: This is a data set of the paper.
DOI: 10.5281/zenodo.3515127
title: data set

description: This is a data set of the paper.
DOI: 10.15468/iwxmsc
title: Integrating data to redescribe Euschistus taurulus Berg (Hemiptera: Pentatomidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Hickmann, Frederico, Moraes, Tamara, Bianchi, Filipe Michels, Corrêa, Alberto Soares, Schwertner, Cristiano Feldens (2019): Integrating data to redescribe Euschistus taurulus Berg (Hemiptera: Pentatomidae). Zootaxa 4688 (1): 119-134, DOI: https://doi.org/10.11646/zootaxa.4688.1.7
DOI: 10.15468/np0at5
title: A new genus Microsarimodes with one species from Hainan Province in China (Hemiptera: Fulgoromorpha: Issidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Chang, Zhi-Min, Yang, Lin, Chen, Xiang-Sheng (2019): A new genus Microsarimodes with one species from Hainan Province in China (Hemiptera: Fulgoromorpha: Issidae). Zootaxa 4688 (1): 135-143, DOI: https://doi.org/10.11646/zootaxa.4688.1.8
DOI: 10.7910/dvn/mwelod/hwhlwi
title: code.rar

description: :unav
DOI: 10.7910/dvn/mwelod/qdagcc
title: readme.pdf

description: :unav
DOI: 10.15468/nqlfz9
title: A new species of Apostlethrips (Thysanoptera, Phlaeothripidae); an Australian genus from grass tussocks

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wang, Jun, Mound, Laurence, Tree, Desley J. (2019): A new species of Apostlethrips (Thysanoptera, Phlaeothripidae); an Australian genus from grass tussocks. Zootaxa 4688 (1): 144-146, DOI: https://doi.org/10.11646/zootaxa.4688.1.9
DOI: 10.15784/601218
title: Last Interglacial Mean Ocean Temperature

description: Noble gas data from Taylor Glacier and EPICA Dome C (EDC) for mean ocean temperature reconstruction during the Last Interglacial. Also includes trace gas measurements of d18Oatm, CO2, and CH4 from Taylor Glacier from chronology construction.
DOI: 10.18152/moredata/366
title: KITT+. Datensammlung

description: [MoReData.Quality] Value=50
description: [MoReData.Quality] Nr=78
DOI: 10.21227/wmps-x759
title: A Machine Learning Benchmark for Facies Classification

description: The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As a result, researchers have often resorted to annotating their own training and testing data. However, different researchers may annotate different classes, or use different train and test splits. In addition, it is common for papers that apply deep learning for facies classification to not contain quantitative results, and rather rely solely on visual inspection of the results. All of these practices have lead to subjective results and have greatly hindered the ability to compare different machine learning models against each other and understand the advantages and disadvantages of each approach.To address these issues, we open-source an accurate 3D geological model of the Netherlands F3 Block. This geological model is based on both well log data and 3D seismic data and is grounded on the careful study of the geology of the region. Furthermore, we propose two baseline models for facies classification based on deconvolution networks and make their codes publicly available. Finally, we propose a scheme for evaluating different models on this dataset, and we share the results of our baseline models. In addition to making the dataset and the code publicly available, this work can help advance research in this area and create an objective benchmark for comparing the results of different machine learning approaches for facies classification for researchers to use in the future.
DOI: 10.5066/p9vsfc7j
title: Wolf Hematology in the Superior National Forest, 1989-1993

description: Hematology and body mass were studied in nine female and five male free-ranging wolves in the Superior National Forest handled 4-17 times during 1989-1993. The dataset includes the following data for each wolf studied: wolf identifier, dates caught, sex, age, body mass in kg, adjusted body mass in kg, and values of hemoglobin (Hb), red blood cells (RBC), mean corpuscular hemoglobin (MCH), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), and white blood cells (WBC).
DOI: 10.21227/89bg-vh96
title: A Machine Learning Benchmark for Facies Classification

description: The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As a result, researchers have often resorted to annotating their own training and testing data. However, different researchers may annotate different classes, or use different train and test splits. In addition, it is common for papers that apply deep learning for facies classification to not contain quantitative results, and rather rely solely on visual inspection of the results. All of these practices have lead to subjective results and have greatly hindered the ability to compare different machine learning models against each other and understand the advantages and disadvantages of each approach.To address these issues, we open-source an accurate 3D geological model of the Netherlands F3 Block. This geological model is based on both well log data and 3D seismic data and is grounded on the careful study of the geology of the region. Furthermore, we propose two baseline models for facies classification based on deconvolution networks and make their codes publicly available. Finally, we propose a scheme for evaluating different models on this dataset, and we share the results of our baseline models. In addition to making the dataset and the code publicly available, this work can help advance research in this area and create an objective benchmark for comparing the results of different machine learning approaches for facies classification for researchers to use in the future.
DOI: 10.5281/zenodo.3514910
title: scRNA-seq dataset prefiltered from Paul et al. (2015), Cell

description: Preprocessed dataset from Paul et al. (2015), Cell, to use for tradeSeq vignette.
DOI: 10.21227/s7ys-ac91
title: A Machine Learning Benchmark for Facies Classification

description: The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As a result, researchers have often resorted to annotating their own training and testing data. However, different researchers may annotate different classes, or use different train and test splits. In addition, it is common for papers that apply deep learning for facies classification to not contain quantitative results, and rather rely solely on visual inspection of the results. All of these practices have lead to subjective results and have greatly hindered the ability to compare different machine learning models against each other and understand the advantages and disadvantages of each approach.To address these issues, we open-source an accurate 3D geological model of the Netherlands F3 Block. This geological model is based on both well log data and 3D seismic data and is grounded on the careful study of the geology of the region. Furthermore, we propose two baseline models for facies classification based on deconvolution networks and make their codes publicly available. Finally, we propose a scheme for evaluating different models on this dataset, and we share the results of our baseline models. In addition to making the dataset and the code publicly available, this work can help advance research in this area and create an objective benchmark for comparing the results of different machine learning approaches for facies classification for researchers to use in the future.
DOI: 10.5281/zenodo.3508636
title: Improving quality of life among healthy individuals through theatre activities: a theatre-in-health pilot project

description: <strong>Background</strong> Review of previous studies regarding arts and health reveals knowledge gaps regarding the use of theatre activities outside a clinical setting with healthy participants. The purpose of this study was to evaluate quality of life benefits of structured theatre training improvisations among generally healthy individuals. <strong>Methods</strong> A mixed methods approach was used at three theatre activities workshops. Pre- and post-quality of life surveys were completed at administered at each workshop. workshop. Participants also free wrote after the workshops, reflecting on their experiences. <strong>Results</strong> The surveys showed that there was a statistically significant shift in a positive direction in each domain studied. Themes that emerged from the free-writing responses were those of play, social acceptance, gratitude, and community. <strong>Conclusions</strong> Findings demonstrate that structured theatre activities produce quality of life benefits across all domains. This pilot study indicates the potential for such theatre-in-health projects as a tool for quality of life improvement.