cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24849711
title: Apple tree images for trunk detection experiments (YOLOv8 format)

description: This dataset is designed for tree trunk detection in orchard environments using the YOLOv8 format. The dataset focuses apple trees, providing a comprehensive collection of images captured in orchards. The images cover various lighting conditions, weather scenarios, and seasonal changes to ensure robust model performance.The dataset consists of 1580 training images and 176 validation images.<br>
DOI: 10.5281/zenodo.10393561
title: Simulations from "Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors"

description: IL6R/IL8R Antibody Binding Model Code

Christina M.P. Ray, Huilin Yang, Jamie B. Spangler, Feilim Mac Gabhann

This dataset contains all simulation output files generated for the article "Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors". The model is comprised of a coupled set of ordinary differential equations (ODEs) where each individual ODE describes one molecule (antibody or receptor) or molecular complex (antibody + receptor). The terms in the ODEs represent each binding interaction (binding and unbinding processes) in the system.

The code for the binding model and for the analysis and visualization results is available on GitHub at christyray/bispecific-binding-model.

Specific Simulations

The .csv and  .rds files in the correspond to the results from the simulations performed for the article "Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors". These files can be read into R using the import_data() function included in the GitHub repository.

The id files contain simulation IDs to link the molecule concentrations (yin) and parameter values (params) with the simulation results (out). When applicable, the norm files contain normalized simulation output, and the occupied files contain receptor fractional occupancy values calculated from the simulation output.



optimization: Optimization of binding rate constants (association and dissociation) to experimental in vitro flow cytometry data; results displayed in Figure 2

binding-curve: Model simulations using the best-fit parameter set for comparison to the experimental data used to fit the model parameters; results displayed in Figure 3

compare-opt: Model simulations using each of the optimized parameter sets; results displayed in the Supplemental Information

time: Simulations of antibody binding dynamics over time; results displayed in Figure 4

concentration: Simulations with varying antibody concentrations and receptor expression levels; results displayed in Figure 5

monovalent: Simulations restricted to monovalent antibody binding only; results displayed in Figure 6

compare-ab and compare-recep: Simulations of both the bispecific antibody BS1 and the combination of monospecific antibodies tocilizumab and 10H2 for comparsion; results displayed in Figure 7

local and global: Local and global univariate sensitivity analyses; results displayed in Figure 8


References



H. Yang, M. N. Karl, W. Wang, B. Starich, H. Tan, A. Kiemen, A. B. Pucsek, Y.-H. Kuo, G. C. Russo, T. Pan, E. M. Jaffee, E. J. Fertig, D. Wirtz, and J. B. Spangler. Engineered bispecific antibodies targeting the interleukin-6 and -8 receptors potently inhibit cancer cell migration and tumor metastasis. Molecular Therapy, 30(11):3430–3449, Nov. 2022. doi:10.1016/j.ymthe.2022.07.008
DOI: 10.5281/zenodo.10393562
title: Simulations from "Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors"

description: IL6R/IL8R Antibody Binding Model Code

Christina M.P. Ray, Huilin Yang, Jamie B. Spangler, Feilim Mac Gabhann

This dataset contains all simulation output files generated for the article "Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors". The model is comprised of a coupled set of ordinary differential equations (ODEs) where each individual ODE describes one molecule (antibody or receptor) or molecular complex (antibody + receptor). The terms in the ODEs represent each binding interaction (binding and unbinding processes) in the system.

The code for the binding model and for the analysis and visualization results is available on GitHub at christyray/bispecific-binding-model.

Specific Simulations

The .csv and  .rds files in the correspond to the results from the simulations performed for the article "Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors". These files can be read into R using the import_data() function included in the GitHub repository.

The id files contain simulation IDs to link the molecule concentrations (yin) and parameter values (params) with the simulation results (out). When applicable, the norm files contain normalized simulation output, and the occupied files contain receptor fractional occupancy values calculated from the simulation output.



optimization: Optimization of binding rate constants (association and dissociation) to experimental in vitro flow cytometry data; results displayed in Figure 2

binding-curve: Model simulations using the best-fit parameter set for comparison to the experimental data used to fit the model parameters; results displayed in Figure 3

compare-opt: Model simulations using each of the optimized parameter sets; results displayed in the Supplemental Information

time: Simulations of antibody binding dynamics over time; results displayed in Figure 4

concentration: Simulations with varying antibody concentrations and receptor expression levels; results displayed in Figure 5

monovalent: Simulations restricted to monovalent antibody binding only; results displayed in Figure 6

compare-ab and compare-recep: Simulations of both the bispecific antibody BS1 and the combination of monospecific antibodies tocilizumab and 10H2 for comparsion; results displayed in Figure 7

local and global: Local and global univariate sensitivity analyses; results displayed in Figure 8


References



H. Yang, M. N. Karl, W. Wang, B. Starich, H. Tan, A. Kiemen, A. B. Pucsek, Y.-H. Kuo, G. C. Russo, T. Pan, E. M. Jaffee, E. J. Fertig, D. Wirtz, and J. B. Spangler. Engineered bispecific antibodies targeting the interleukin-6 and -8 receptors potently inhibit cancer cell migration and tumor metastasis. Molecular Therapy, 30(11):3430–3449, Nov. 2022. doi:10.1016/j.ymthe.2022.07.008
DOI: 10.13012/b2idb-2436375_v1
title: Meterology and ocean data collected at LSU WAVCIS Lab

description: This dataset includes both meteorology and oceanography data collected at stations (CSI03, CSI06, and CSI09) near the Gulf of Mexico from the LSU WAVCIS (Waves-Current-Surge Information System) lab. The associated data analysis visualization is also saved in separate directories.
DOI: 10.5281/zenodo.10402822
title: Suplementary Material for Direct hydrodynamic measurements at the upper shoreface of a sandy beach in Paraná - Brazil

description: ADCP data accompanying the manuscript entitled "Direct hydrodynamic measurements at the upper shoreface of a sandy beach in Paraná - Brazil" to be published in Ocean and Coastal Research (ISSN (online): 2675-2824)
description: Instrument: 750 kHz ADCP SonTek/YSI Inc Argonaut XR model

Mooring position: Lat.: 25.725944 S; Long.: 48.482992 W

Mooring depth: 5 m

Depth-integrated current data starting at 1.1 m from the sea bottom

Sample interval: 15 min

Magnetic declination: Corrected
DOI: 10.5281/zenodo.10402823
title: Suplementary Material for Direct hydrodynamic measurements at the upper shoreface of a sandy beach in Paraná - Brazil

description: ADCP data accompanying the manuscript entitled "Direct hydrodynamic measurements at the upper shoreface of a sandy beach in Paraná - Brazil" to be published in Ocean and Coastal Research (ISSN (online): 2675-2824)
description: Instrument: 750 kHz ADCP SonTek/YSI Inc Argonaut XR model

Mooring position: Lat.: 25.725944 S; Long.: 48.482992 W

Mooring depth: 5 m

Depth-integrated current data starting at 1.1 m from the sea bottom

Sample interval: 15 min

Magnetic declination: Corrected
DOI: 10.5281/zenodo.7522339
title: U.S. Science Journalists' Knowledge and Opinion of Open Access Articles as Sources

description: Survey data of U.S. science journalists and their knowledge and opinions of OA research as news sources.
DOI: 10.5281/zenodo.7522340
title: U.S. Science Journalists' Knowledge and Opinion of Open Access Articles as Sources

description: Survey data of U.S. science journalists and their knowledge and opinions of OA research as news sources.
DOI: 10.5281/zenodo.10211698
title: SSCS and DCS fq data for NZB conplastic mice mitochondrial DNA profiling

description: The SSCS and DCS fq files for NZB conplastic mice associated with https://doi.org/10.5281/zenodo.10127101 repo.
DOI: 10.5281/zenodo.10211699
title: SSCS and DCS fq data for NZB conplastic mice mitochondrial DNA profiling

description: The SSCS and DCS fq files for NZB conplastic mice associated with https://doi.org/10.5281/zenodo.10127101 repo.
DOI: 10.5281/zenodo.10294450
title: SSCS and DCS fastq data for FVB conplastic mice mitochondrial DNA profiling

description: The SSCS and DCS fq files for FVB conplastic mice associated with https://doi.org/10.5281/zenodo.10127101 repo.
DOI: 10.5281/zenodo.10294451
title: SSCS and DCS fastq data for FVB conplastic mice mitochondrial DNA profiling

description: The SSCS and DCS fq files for FVB conplastic mice associated with https://doi.org/10.5281/zenodo.10127101 repo.
DOI: 10.5281/zenodo.10402574
title: Copper mineralization at Carajás mineral province - Brazil: geological, structural, and geophysical data

description: Gridded geological, structural, and geophysical data at the Carajás mineral province. A number of known Cu occurrences are provided. This dataset is suitable for experimenting with machine learning methods.
DOI: 10.5281/zenodo.10402573
title: Copper mineralization at Carajás mineral province - Brazil: geological, structural, and geophysical data

description: Gridded geological, structural, and geophysical data at the Carajás mineral province. A number of known Cu occurrences are provided. This dataset is suitable for experimenting with machine learning methods.
DOI: 10.5281/zenodo.10403021
title: REQUIREMENTS FOR PSYCHOLOGICAL AND PEDAGOGICAL TRAINING OF CADETS OF HIGHER MILITARY EDUCATIONAL INSTITUTIONS
DOI: 10.5281/zenodo.10403020
title: REQUIREMENTS FOR PSYCHOLOGICAL AND PEDAGOGICAL TRAINING OF CADETS OF HIGHER MILITARY EDUCATIONAL INSTITUTIONS
DOI: 10.5281/zenodo.10403026
title: Dataset - Open IDs of Tweets containing data on Healthy food
DOI: 10.5281/zenodo.10403027
title: Dataset - Open IDs of Tweets containing data on Healthy food
DOI: 10.34740/kaggle/dsv/7232720
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.10403030
title: ПЕДОФИЛИЯ ТУШУНЧАСИ, РИВОЖЛАНИШ ТАРИХИ ВА ИЖТИМОИЙ ХАВФЛИЛИГИ
DOI: 10.5281/zenodo.10403031
title: ПЕДОФИЛИЯ ТУШУНЧАСИ, РИВОЖЛАНИШ ТАРИХИ ВА ИЖТИМОИЙ ХАВФЛИЛИГИ
DOI: 10.5281/zenodo.10392212
title: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints"

description: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints".

This version contains a single compressed archive to mainatin the directory structure.
DOI: 10.5281/zenodo.10392213
title: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints"

description: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints"
DOI: 10.5281/zenodo.10402691
title: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints"

description: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints"
DOI: 10.5281/zenodo.10403049
title: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints"

description: Replication package for paper "Deepen REST API Black-box Testing: Leveraging Deep Reinforcement Learning to Exploit Hidden API Constraints".

This version contains a single compressed archive to mainatin the directory structure.
DOI: 10.5281/zenodo.8280126
title: HUSM and GMicro: PPG Peak detection

description: Photoplethysmography (PPG) is a non-invasive technique that measures changes in blood flow volume through optical means. Accurate detection of peaks in the PPG waveform allows the extraction of the heart rate variability (HRV), a recognized indicator for the health of the cardiac and autonomic nervous systems. We make available a novel dataset comprising 66 minutes of PPG recordings from healthy individuals and patients with cardiopulmonary diseases, in three distinct phases of an acquisition protocol, with annotations for every systolic peak present.

The dataset composition and organization are detailed in the paper that acompanies the dataset.
description: Paper which describes the dataset acquisition and usage:

@misc{machado2023srmac,      title={SRMAC -- Smoothed Recursive Moving Average Crossover for Real-Time Systolic Peak Detection in Photoplethysmography},       author={Cesar Abascal Machado and Victor O. Costa and Cesar Augusto Prior and Cesar Ramos Rodrigues},      year={2023},      eprint={2312.10013},      archivePrefix={arXiv},      primaryClass={eess.SP}}


Git repository with the source code used in the implementation and test of a recursive peak detector: https://github.com/GMicro-uPPG/SRMAC_peak_detector.
DOI: 10.5281/zenodo.8280127
title: HUSM and GMicro: PPG Peak detection

description: Photoplethysmography (PPG) is a non-invasive technique that measures changes in blood flow volume through optical means. Accurate detection of peaks in the PPG waveform allows the extraction of the heart rate variability (HRV), a recognized indicator for the health of the cardiac and autonomic nervous systems. We make available a novel dataset comprising 66 minutes of PPG recordings from healthy individuals and patients with cardiopulmonary diseases, in three distinct phases of an acquisition protocol, with annotations for every systolic peak present.

The dataset composition and organization are detailed in the paper that acompanies the dataset.
description: Paper which describes the dataset acquisition and usage:

@misc{machado2023srmac,      title={SRMAC -- Smoothed Recursive Moving Average Crossover for Real-Time Systolic Peak Detection in Photoplethysmography},       author={Cesar Abascal Machado and Victor O. Costa and Cesar Augusto Prior and Cesar Ramos Rodrigues},      year={2023},      eprint={2312.10013},      archivePrefix={arXiv},      primaryClass={eess.SP}}


Git repository with the source code used in the implementation and test of a recursive peak detector: https://github.com/GMicro-uPPG/SRMAC_peak_detector.
DOI: 10.5281/zenodo.10403062
title: PEDAGOGIK INNOVATSIYALARNI TASNIFLASHDA TURLICHA YONDASHUVLAR
DOI: 10.5281/zenodo.10403063
title: PEDAGOGIK INNOVATSIYALARNI TASNIFLASHDA TURLICHA YONDASHUVLAR
DOI: 10.5281/zenodo.10403068
title: THE ROLE OF ELECTRICITY PRODUCING ENTERPRISES IN THE DEVELOPMENT OF THE ENERGY SECTOR OF THE REPUBLIC
DOI: 10.5281/zenodo.10403069
title: THE ROLE OF ELECTRICITY PRODUCING ENTERPRISES IN THE DEVELOPMENT OF THE ENERGY SECTOR OF THE REPUBLIC
DOI: 10.7274/24855846
title: Top 20 Departments

description: Ranking Relevance, II project
DOI: 10.7274/24855846.v1
title: Top 20 Departments

description: Ranking Relevance, II project
DOI: 10.5281/zenodo.10403076
title: Supplementary Document
DOI: 10.5281/zenodo.10403077
title: Supplementary Document
DOI: 10.5281/zenodo.10397996
title: SSCS and DCS fastq data for ALR conplastic mice mitochondrial DNA profiling

description: The SSCS and DCS fq files for ALR conplastic mice associated with https://doi.org/10.5281/zenodo.10127101 repo.
DOI: 10.5281/zenodo.10397997
title: SSCS and DCS fastq data for ALR conplastic mice mitochondrial DNA profiling

description: The SSCS and DCS fq files for ALR conplastic mice associated with https://doi.org/10.5281/zenodo.10127101 repo.
DOI: 10.5281/zenodo.10403070
title: Data - Krieg et al. Greater ecophysiological stress tolerance in the core environment than in extreme environments of wild chickpea (Cicer reticulatum)

description: Data used in analyses and code to produce figures.
DOI: 10.5281/zenodo.10403071
title: Data - Krieg et al. Greater ecophysiological stress tolerance in the core environment than in extreme environments of wild chickpea (Cicer reticulatum)

description: Data used in analyses and code to produce figures.
DOI: 10.5281/zenodo.10402963
title: Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

description: Files (input and output) for the publication Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems
DOI: 10.5281/zenodo.10402964
title: Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

description: Files (input and output) for the publication Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems
DOI: 10.13012/b2idb-7860393_v1
title: Supporting data processing scripts and example data for Peru AIDData analysis

description: Scripts and example data for AIDData (aiddata.org) processing in support of forthcoming Nakamura dissertation.

This dataset includes two sets of scripts and example data files from an aiddata.org data dump. Fuller documentation about the functionality for these scripts is within the readme file. Additional background information and description of usage will be in the forthcoming Nakamura dissertation (link will be added when available). Data originally supplied by Nakamura. Python code and this readme file created by Wickes. Data included within this deposit are examples to demonstrate execution.

Roughly, there are two python scripts in here: keyword_search.py, designed to assist in finding records matching specific keywords, and matching_tool.ipynb, designed to assist in detection of which records are and are not contained within a keyword results file and an aiddata project data file.
DOI: 10.25505/fiz.icsd.cc21gqlv
title: CSD 1890987: Experimental Crystal Structure Determination

description: Related Article: Abdessalem Badri, Meriem Bembli, Inmaculada Alvarez-Serrano, María Luisa López, Mongi Ben Amara|2023|J.Solid State Chem.|325|124141|doi:10.1016/j.jssc.2023.124141
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc220cp5
title: CSD 1906986: Experimental Crystal Structure Determination

description: Related Article: Qian Wang, Lei Wang, Xiaoyu Zhao, Ling Huang, Daojiang Gao, Jian Bi, Xin Wang, Guohong Zou|2019|Inorg.Chem.Front.|6|3125|doi:10.1039/C9QI01036J
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc21kj16
title: CSD 1893667: Experimental Crystal Structure Determination

description: Related Article: Sergey M. Aksenov, Stephanie A. Mackley, Dina V. Deyneko, Vladimir K. Taroev, Vladimir L. Tauson, Ramiza K. Rastsvetaeva, Peter C. Burns|2019|Microporous and Mesoporous Materials|284|25|doi:10.1016/j.micromeso.2019.04.006
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc22yqpg
title: CSD 1935196: Experimental Crystal Structure Determination

description: Related Article: Zhangbin Song, Tong Liu, Yan Liu, Bin Zhang, Shasha Song, Zengdian Zhao|2023|J.Solid State Chem.|318|123716|doi:10.1016/j.jssc.2022.123716
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25505/fiz.icsd.cc220cn4
title: CSD 1906985: Experimental Crystal Structure Determination

description: Related Article: Qian Wang, Lei Wang, Xiaoyu Zhao, Ling Huang, Daojiang Gao, Jian Bi, Xin Wang, Guohong Zou|2019|Inorg.Chem.Front.|6|3125|doi:10.1039/C9QI01036J
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.10402842
title: Datasets for Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar

description: These datasets accompany the analyses conducted under the study title "Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar"

Accompanying R scripts with commentary to run these data can be found in the Github repository under release v1.0.0: https://github.com/bmtalbot/Humans_and_Lemurs_2017
DOI: 10.5281/zenodo.10402843
title: Datasets for Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar

description: These datasets accompany the analyses conducted under the study title "Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar"

Accompanying R scripts with commentary to run these data can be found in the Github repository under release v1.0.0: https://github.com/bmtalbot/Humans_and_Lemurs_2017
DOI: 10.7274/24856155
title: Top 50 Departments All Measures

description: Ranking Relevance, II project
DOI: 10.7274/24856155.v1
title: Top 50 Departments All Measures

description: Ranking Relevance, II project