cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive104421.20180622.3
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive104422.20180622.3
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive104423.20180622.3
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive104424.20180622.3
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive104425.20180622.3
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105232.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105233.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105234.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105235.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105236.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105237.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105238.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive105239.20180622.3
title: Gordonia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106038.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106039.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106040.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106041.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106042.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106043.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106044.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106045.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106861.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106862.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106863.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106864.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106865.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106866.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106867.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106868.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive106869.20180622.3
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive101064.20180622.3
title: Clavibacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive101065.20180622.3
title: Clavibacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive101066.20180622.3
title: Clavibacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive101067.20180622.3
title: Clavibacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive101068.20180622.3
title: Clavibacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive101069.20180622.3
title: Clavibacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.6513014
title: Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

description: Generated training sets: training_set_supp_table6.zip training_set_supp_table7.zip training_set_supp_table8.zip training_set_supp_table9.zip training_set_supp_table10.zip training_set_supp_table11.zip Trained weights of experimental data: training_result_supp_table7.zip training_result_supp_table8.zip training_result_supp_table9.zip training_result_supp_table10.zip training_result_supp_table11.zip Simulation results: Simulation_results.zip Experimental results: Human_bone_marrow_IMC_denoising_results.zip Human_breast_cancer_IMC_denoising_results.zip Human_pancreatic_cancer_IMC_denoising_results.zip MIBI_denoising_results.zip Ilastik-processed or manual-labeled results: DIMR_Ilastik_results.zip background_removal_results.zip manual_annotated_public_datasets.zip Extracted single cell data and the corresponding phenotyping results from both DIMR and DeepSNiF-based segmented cell masks: Single_cell_analysis.zip
DOI: 10.5281/zenodo.6513015
title: Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

description: Trained weights of experimental data; Generated simulation results; Ilastik-processed results; Extracted single cell data
DOI: 10.5281/zenodo.6516116
title: Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

description: Generated training sets: training_set_supp_table6.zip training_set_supp_table7.zip training_set_supp_table8.zip training_set_supp_table9.zip training_set_supp_table10.zip training_set_supp_table11.zip Trained weights of experimental data: training_result_supp_table7.zip training_result_supp_table8.zip training_result_supp_table9.zip training_result_supp_table10.zip training_result_supp_table11.zip Simulation results: Simulation_results.zip Experimental results: Human_bone_marrow_IMC_denoising_results.zip Human_breast_cancer_IMC_denoising_results.zip Human_pancreatic_cancer_IMC_denoising_results.zip MIBI_denoising_results.zip Ilastik-processed results: DIMR_Ilastik_results.zip background_removal_results.zip Extracted single cell data and the corresponding phenotyping results: single_cell_analysis.zip
DOI: 10.5281/zenodo.7084466
title: Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

description: Generated training sets: training_set_supp_table6.zip training_set_supp_table7.zip training_set_supp_table8.zip training_set_supp_table9.zip training_set_supp_table10.zip training_set_supp_table11.zip Trained weights of experimental data: training_result_supp_table7.zip training_result_supp_table8.zip training_result_supp_table9.zip training_result_supp_table10.zip training_result_supp_table11.zip Simulation results: Simulation_results.zip Experimental results: Human_bone_marrow_IMC_denoising_results.zip Human_breast_cancer_IMC_denoising_results.zip Human_pancreatic_cancer_IMC_denoising_results.zip MIBI_denoising_results.zip Ilastik-processed or manual-labeled results: DIMR_Ilastik_results.zip background_removal_results.zip manual_annotated_public_datasets.zip Extracted single cell data and the corresponding phenotyping results: single_cell_analysis.zip
DOI: 10.5281/zenodo.7101454
title: Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

description: Generated training sets: training_set_supp_table6.zip training_set_supp_table7.zip training_set_supp_table8.zip training_set_supp_table9.zip training_set_supp_table10.zip training_set_supp_table11.zip Trained weights of experimental data: training_result_supp_table7.zip training_result_supp_table8.zip training_result_supp_table9.zip training_result_supp_table10.zip training_result_supp_table11.zip Simulation results: Simulation_results.zip Experimental results: Human_bone_marrow_IMC_denoising_results.zip Human_breast_cancer_IMC_denoising_results.zip Human_pancreatic_cancer_IMC_denoising_results.zip MIBI_denoising_results.zip Ilastik-processed or manual-labeled results: DIMR_Ilastik_results.zip background_removal_results.zip manual_annotated_public_datasets.zip Extracted single cell data and the corresponding phenotyping results: single_cell_analysis.zip
DOI: 10.5281/zenodo.7336448
title: Results of IMC-Denoise: a content aware pipeline to enhance Imaging Mass Cytometry

description: Generated training sets: training_set_supp_table6.zip training_set_supp_table7.zip training_set_supp_table8.zip training_set_supp_table9.zip training_set_supp_table10.zip training_set_supp_table11.zip Trained weights of experimental data: training_result_supp_table7.zip training_result_supp_table8.zip training_result_supp_table9.zip training_result_supp_table10.zip training_result_supp_table11.zip Simulation results: Simulation_results.zip Experimental results: Human_bone_marrow_IMC_denoising_results.zip Human_breast_cancer_IMC_denoising_results.zip Human_pancreatic_cancer_IMC_denoising_results.zip MIBI_denoising_results.zip Ilastik-processed or manual-labeled results: DIMR_Ilastik_results.zip background_removal_results.zip manual_annotated_public_datasets.zip Extracted single cell data and the corresponding phenotyping results from both DIMR and DeepSNiF-based segmented cell masks: Single_cell_analysis.zip
DOI: 10.5281/zenodo.5719772
title: InfoGenomeR T47D

description: T47D data for InfoGenomeR
DOI: 10.5517/ccdc.csd.cc29z9m7
title: CCDC 2144289: Experimental Crystal Structure Determination

description: Related Article: Haitao Cui, Caijin Ban, Fengting Zhu, Jingmei Yuan, Juan Du, Yanmin Huang, Qi Xiao, Chusheng Huang, Jun Huang, Qiang Zhu|2022|Org.Lett.|25|99|doi:10.1021/acs.orglett.2c03907
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.7559331
title: clarias_angolensis_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7559330
title: clarias_angolensis_zanfona_1.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/4885826
title: US counties COVID 19 dataset
DOI: 10.6084/m9.figshare.21938342
title: Referencias y Fuentes

description: Data about most relevant sources most relevant authors <br> topic: Innovation and open science
DOI: 10.6084/m9.figshare.21938342.v1
title: Referencias y Fuentes

description: Data about most relevant sources most relevant authors <br> topic: Innovation and open science
DOI: 10.6084/m9.figshare.21938351
title: Autores

description: Most productive authors Topic: Innovation and open science
DOI: 10.6084/m9.figshare.21938351.v1
title: Autores

description: Most productive authors Topic: Innovation and open science
DOI: 10.5281/zenodo.7558670
title: 2D LSFM timelapse of cardiomyocyte calcium dynamics

description: Uploaded zip-folder contains the following files:<br> 1. A representative raw dataset of a 2D LSFM ventricular cardiomyocyte undergoing stimulated calcium transients and calcium sparks (frame_0000.tif -frame_17999.tif)<br> 2. The recorded pacing signal time trace (waveform_test.xslx)<br> 3. Image corresponding to the time-averaged background (AVG_19_35_39_LowNA rolling shutter.tif)<br> 4. Pre-processed nuclear mask matrix (NuclearMask.mat), CMO-channel average (CMO_Average.mat), and CMO channel maximum intensity projection (CMO_MIP). <br> 5. Split and co-registered data for each spectral channel (CMO_frame_00001.tif-CMO_frame_18000.tif, FLUO4_frame_00001.tif -FLUO4_frame_18000.tif).<br> <br> Compressed file size: 14.9 GB<br> Uncompressed file size: 42.8 GB. <br> <br> Related to the following manuscript: <br> Liuba Dvinskikh, Hugh Sparks, Ken MacLeod and Chris Dunsby " <em>High-speed 2D light-sheet fluorescence microscopy enables quantification of spatially varying calcium dynamics in ventricular cardiomyocytes</em>" (2023), <em>In review</em> with Frontiers in Physiology, Cardiac Electrophysiology.
description: This version has been updated to include processed split and co-registered data for each spectral channel.
DOI: 10.5281/zenodo.7558671
title: 2D LSFM timelapse of cardiomyocyte calcium dynamics

description: Uploaded zip-folder contains the following files:<br> 1. A representative raw dataset of a 2D LSFM ventricular cardiomyocyte undergoing stimulated calcium transients and calcium sparks (frame_0000.tif -frame_17999.tif)<br> 2. The recorded pacing signal time trace (waveform_test.xslx)<br> 3. Image corresponding to the time-averaged background (AVG_19_35_39_LowNA rolling shutter.tif)<br> 4. Pre-processed nuclear mask matrix (NuclearMask.mat), CMO-channel average (CMO_Average.mat), and CMO channel maximum intensity projection (CMO_MIP). <br> <br> Compressed file size: 8.8 GB<br> Uncompressed file size: 20.8 GB. <br> <br> Related to the following manuscript: <br> Liuba Dvinskikh, Hugh Sparks, Ken MacLeod and Chris Dunsby " <em>High-speed 2D light-sheet fluorescence microscopy enables quantification of spatially varying calcium dynamics in ventricular cardiomyocytes</em>" (2023), <em>In review</em> with Frontiers in Physiology, Cardiac Electrophysiology.
DOI: 10.5281/zenodo.7559264
title: 2D LSFM timelapse of cardiomyocyte calcium dynamics

description: Uploaded zip-folder contains the following files:<br> 1. A representative raw dataset of a 2D LSFM ventricular cardiomyocyte undergoing stimulated calcium transients and calcium sparks (frame_0000.tif -frame_17999.tif)<br> 2. The recorded pacing signal time trace (waveform_test.xslx)<br> 3. Image corresponding to the time-averaged background (AVG_19_35_39_LowNA rolling shutter.tif)<br> 4. Pre-processed nuclear mask matrix (NuclearMask.mat), CMO-channel average (CMO_Average.mat), and CMO channel maximum intensity projection (CMO_MIP). <br> 5. Split and co-registered data for each spectral channel (CMO_frame_00001.tif-CMO_frame_18000.tif, FLUO4_frame_00001.tif -FLUO4_frame_18000.tif).<br> <br> Compressed file size: 14.9 GB<br> Uncompressed file size: 42.8 GB. <br> <br> Related to the following manuscript: <br> Liuba Dvinskikh, Hugh Sparks, Ken MacLeod and Chris Dunsby " <em>High-speed 2D light-sheet fluorescence microscopy enables quantification of spatially varying calcium dynamics in ventricular cardiomyocytes</em>" (2023), <em>In review</em> with Frontiers in Physiology, Cardiac Electrophysiology.
description: This version has been updated to include processed split and co-registered data for each spectral channel.
DOI: 10.5281/zenodo.7559345
title: InfoHiC T47D

description: InfoHiC T47D data (Hi-C matrix)
DOI: 10.5281/zenodo.7559344
title: InfoHiC T47D

description: InfoHiC T47D data (Hi-C matrix)
DOI: 10.5281/zenodo.7275057
title: INDRA assembly Benchmark Corpus

description: This data set accompanies the manuscript "Automated assembly of molecular mechanisms at scale from text mining and curated databases" which describes assembly methodology implemented in the INDRA system (https://github.com/sorgerlab/indra). The manuscript uses an example assembly pipeline on ~570k publications as input to create the INDRA Benchmark Corpus. This dataset provides INDRA Statements constituting the INDRA Benchmark Corpus as well as a set of curations on the corpus: - indra_benchmark_corpus.pkl: A Python pickle file of INDRA Statement objects. It requires INDRA to be installed to load in a Python environment. - indra_benchmark_corpus.json.gz: A gzipped JSON export of INDRA Statements. - indra_assembly_curations.json: The Curated Corpus of curated mentions for Statements in Benchmark Corpus as a JSON file. The JSON file contains a list with each element corresponding to a curation. Each curation entry contains a `pa_hash` and a `source_hash` attribute. These can be used to find the Statement and mention (respectively) to which the curation applies in the Benchmark Corpus.
DOI: 10.5281/zenodo.7275058
title: INDRA assembly Benchmark Corpus

description: This data set accompanies the manuscript "Automated assembly of molecular mechanisms at scale from text mining and curated databases" which describes assembly methodology implemented in the INDRA system (https://github.com/sorgerlab/indra). The manuscript uses an example assembly pipeline on ~570k publications as input to create the INDRA Benchmark Corpus. This dataset provides INDRA Statements constituting the INDRA Benchmark Corpus as well as a set of curations on the corpus: - indra_benchmark_corpus.pkl: A Python pickle file of INDRA Statement objects. It requires INDRA to be installed to load in a Python environment. - indra_benchmark_corpus.json.gz: A gzipped JSON export of INDRA Statements. - indra_benchmark_corpus_curations.pkl: Aggregated curations on the Benchmark Corpus as a Python pickle file. The content is a list, where each element of the list is a dictionary providing a stmt_hash corresponding to the hash of a Statement in the Benchmark Corpus, and giving a correct flag (0 for overall incorrect, 1 for overall correct) to represent the overall result of curation, along with some other metadata. - indra_benchmark_corpus_curations.json: Aggregated curations on the Benchmark Corpus as a JSON file.
DOI: 10.5281/zenodo.7559352
title: INDRA assembly Benchmark Corpus

description: This data set accompanies the manuscript "Automated assembly of molecular mechanisms at scale from text mining and curated databases" which describes assembly methodology implemented in the INDRA system (https://github.com/sorgerlab/indra). The manuscript uses an example assembly pipeline on ~570k publications as input to create the INDRA Benchmark Corpus. This dataset provides INDRA Statements constituting the INDRA Benchmark Corpus as well as a set of curations on the corpus: - indra_benchmark_corpus.pkl: A Python pickle file of INDRA Statement objects. It requires INDRA to be installed to load in a Python environment. - indra_benchmark_corpus.json.gz: A gzipped JSON export of INDRA Statements. - indra_assembly_curations.json: The Curated Corpus of curated mentions for Statements in Benchmark Corpus as a JSON file. The JSON file contains a list with each element corresponding to a curation. Each curation entry contains a `pa_hash` and a `source_hash` attribute. These can be used to find the Statement and mention (respectively) to which the curation applies in the Benchmark Corpus.
DOI: 10.5281/zenodo.7559353
title: INDRA assembly Benchmark Corpus

description: This data set accompanies the manuscript "Automated assembly of molecular mechanisms at scale from text mining and curated databases" which describes assembly methodology implemented in the INDRA system (https://github.com/sorgerlab/indra). The manuscript uses an example assembly pipeline on ~570k publications as input to create the INDRA Benchmark Corpus. This dataset provides INDRA Statements constituting the INDRA Benchmark Corpus as well as a set of curations on the corpus: - indra_benchmark_corpus.pkl: A Python pickle file of INDRA Statement objects. It requires INDRA to be installed to load in a Python environment. - indra_benchmark_corpus.json.gz: A gzipped JSON export of INDRA Statements. - indra_assembly_curations.json: The Curated Corpus of curated mentions for Statements in Benchmark Corpus as a JSON file. The JSON file contains a list with each element corresponding to a curation. Each curation entry contains a `pa_hash` and a `source_hash` attribute. These can be used to find the Statement and mention (respectively) to which the curation applies in the Benchmark Corpus.
DOI: 10.7931/v1wc75
title: Waitutu SORTIE-NZ 2001-2008
DOI: 10.17909/33p8-6v73
title: Data used in paper
DOI: 10.5517/ccdc.csd.cc2c72g5
title: CCDC 2181546: Experimental Crystal Structure Determination

description: Related Article: Xiaoxiao Yang, Zhengnan Yuan, Wen Lu, Ce Yang, Minjia Wang, Ravi Tripathi, Zach Fultz, Chalet Tan, Binghe Wang|2022|J.Am.Chem.Soc.|145|78|doi:10.1021/jacs.2c07504
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.