cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3755835
title: SIRAH-CoV2 initiative: Nucleocapsid protein N-terminal RNA binding domain (PDB id:6M3M)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Nucleocapsid protein N-terminal RNA binding domain (PDB id:6M3M). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The files 6M3M_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6M3M_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6M3M_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6M3M_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W4B_SIRAHcg_prot.prmtop 6W4B_SIRAHcg_prot.ncrst 6W4B_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3755834
title: SIRAH-CoV2 initiative: Nucleocapsid protein N-terminal RNA binding domain (PDB id:6M3M)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Nucleocapsid protein N-terminal RNA binding domain (PDB id:6M3M). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The files 6M3M_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6M3M_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6M3M_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6M3M_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W4B_SIRAHcg_prot.prmtop 6W4B_SIRAHcg_prot.ncrst 6W4B_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.25573/data.10059455.v10
title: Monthly Summary_BCI, horizontal

description: Monthly and daily summary from Barro Colorado Island (BCI). Data organized in horizontal format for seasonal and inter-year comparisons<br>Location 9°9'42.36"N, 79°50'15.67"W<br>Parameters: air temperature, relative humidity, wind speed and direction, precipitation, sea surface temperature, solar radiation (pyranometer), air pressure, soil moisture, runoff, potential evapotranspiration, wet/dry season starting dates<br><br>Lutz catchment is a 9.73ha protected watershed on BCIThe Lutz tower was built in 1972 and was originally 42m. In 2002 it was increased to 48m<br>The data from 48m should be considered a separate data series from the data at 42m. Wind speed is significantly higher at 48m due to the distance to the top of the canopy.<br>The Clearing is a small, open area surrounded by forest and some buildings. Station established in 1972. Consists of a Stevenson screen with max/min thermometers and air pressure sensor. Temperature/humidity sensor, rain gauge and evaporation sensors are located at various locations around the screen.
DOI: 10.5281/zenodo.3766270
title: SIRAH-CoV2 initiative: Papain-like Protease (PDB id:6W9C)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Papain-like protease in its APO form with Zn ions bound (PDB id: 6W9C). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Zinc ions were parameterized as reported in Klein et al. 2020. The files 6W9C_SIRAHcg_rawdata_0-5us.tar, 6W9C_SIRAHcg_rawdata_5-10us.tar, contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W9C_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6W9C_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W9C_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W9C_SIRAHcg_prot.prmtop 6W9C_SIRAHcg_prot.ncrst 6W9C_SIRAHcg_10us_prot_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano. Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)", "Machado & Pantano. JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Klein et al. JCIM, 2020 (DOI:10.1021/acs.jcim.0c00160)"]}
DOI: 10.5281/zenodo.3766269
title: SIRAH-CoV2 initiative: Papain-like Protease (PDB id:6W9C)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 Papain-like protease in its APO form with Zn ions bound (PDB id: 6W9C). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Zinc ions were parameterized as reported in Klein et al. 2020. The files 6W9C_SIRAHcg_rawdata_0-5us.tar, 6W9C_SIRAHcg_rawdata_5-10us.tar, contain all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W9C_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6W9C_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W9C_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6W9C_SIRAHcg_prot.prmtop 6W9C_SIRAHcg_prot.ncrst 6W9C_SIRAHcg_10us_prot_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano. Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)", "Machado & Pantano. JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Klein et al. JCIM, 2020 (DOI:10.1021/acs.jcim.0c00160)"]}
DOI: 10.21223/7hiqpg/p7mxmu
title: Malawi Market questionnaire.pdf

description: :unav
DOI: 10.21223/7hiqpg/ns0bik
title: Market Survey.tab

description: :unav
DOI: 10.21223/7hiqpg/ozclvn
title: DataDictionary_Market OFSP Malawi.tab

description: :unav
DOI: 10.21223/7hiqpg
title: Dataset for: Adoption and Effects of Orange-Fleshed Sweetpotato in Malawi (market)

description: International Potato Center (CIP) and partners collaborated to develop orange-fleshed sweetpotato varieties, such as Chipika, Ana-Kwanire, Kadyaubwerere, Mathuthu, Kaphulira and Zondeni . These varieties were formally released in Malawi between 2009 and 2011 and they were heavily promoted by different development organizations in the country. Its success was attributed to its health related attributes, high yield, high seed quality, and good taste. A market survey to Malawian sweetpotato sellers was conducted from May to July 2019. The sample size includes 41 markets located in 34 EPA in 27 Districts. Information was gathered on number of sweetpotato sellers, both OFSP and non-OFSP in the respective markets; quantity sold and price of sweetpotato varieties (Kenya, OFSP, non-OFSP local varieties, mixed local varieties); main sweetpotato substitute and its price. To obtain prices for standard volumes, piles of sweetpotato and cassava roots were weighed using a standard scale
DOI: 10.17632/t68ht4zjc2.1
title: Data for: Visual Learning Curves for American Sign Language (ASL) Alphabet

description: The file contains the experiment data which is the fixation duration per region of interest for all participants per trial for the different letters. It also contains the ration table between the video prompt duration and the mean observation duration per letter for all participants
DOI: 10.5281/zenodo.3779057
title: SIRAH-CoV2 initiative: NSP16 - NSP10 Complex (PDB id:6W4H)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 NSP16 - NSP10 Complex with Zn ions bound (PDB id: 6W4H). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Zinc ions were parameterized as reported in Klein et al. 2020. The file 6W4H_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W4H_SIRAHcg_10us_prot_Zn.tar contains only the protein coordinates, while 6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6w4h_SIRAHcg_prot.prmtop 6w4h_SIRAHcg_prot.ncrst 6w4h_SIRAHcg_prot_Zn_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano, JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano, Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)", "Klein et al., JCIM, 2020 (DOI:10.1021/acs.jcim.0c00160)"]}
DOI: 10.5281/zenodo.3779056
title: SIRAH-CoV2 initiative: NSP16 - NSP10 Complex (PDB id:6W4H)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 NSP16 - NSP10 Complex with Zn ions bound (PDB id: 6W4H). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Zinc ions were parameterized as reported in Klein et al. 2020. The file 6W4H_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W4H_SIRAHcg_10us_prot_Zn.tar contains only the protein coordinates, while 6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6w4h_SIRAHcg_prot.prmtop 6w4h_SIRAHcg_prot.ncrst 6w4h_SIRAHcg_prot_Zn_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano, JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano, Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)", "Klein et al., JCIM, 2020 (DOI:10.1021/acs.jcim.0c00160)"]}
DOI: 10.5281/zenodo.4421499
title: A versatile microfluidic platform measures hyphal interactions between Fusarium graminearum and Clonostachys rosea in real-time

description: Routinely, fungal-fungal interactions (FFIs) are studied on agar surfaces. However, this format restricts high-resolution dynamic imaging. To gain experimental access to FFIs at the hyphal level in real-time, we developed a microfluidic platform, a FFI device. This device utilises microchannel geometry to enhance the visibility of hyphal growth and provides control channels to allow comparisons between localised and systemic effects. We demonstrate its function by investigating the FFI between the biological control agent (BCA) <em>Clonostachys rosea </em>and the plant pathogen <em>Fusarium graminearum. </em>Microscope image analyses confirm the inhibitory effect of the necrotrophic BCA and we show that a loss of fluorescence in parasitised hyphae of GFP-tagged <em>F. graminearum </em>coincides with the detection of GFP in mycelium of <em>C. rosea</em>. The versatility of our device to operate under both water-saturated and nutrient-rich as well as dry and nutrient-deficient conditions, coupled with its spatio-temporal output, opens new opportunities to study relationships between fungi.
DOI: 10.5281/zenodo.3685956
title: A versatile microfluidic platform measures hyphal interactions between Fusarium graminearum and Clonostachys rosea in real-time

description: Routinely, fungal-fungal interactions (FFIs) are studied on agar surfaces. However, this format restricts high-resolution dynamic imaging. To gain experimental access to FFIs at the hyphal level in real-time, we developed a microfluidic platform, a FFI device. This device utilises microchannel geometry to enhance the visibility of hyphal growth and provides control channels to allow comparisons between localised and systemic effects. We demonstrate its function by investigating the FFI between the biological control agent (BCA) <em>Clonostachys rosea </em>and the plant pathogen <em>Fusarium graminearum. </em>Microscope image analyses confirm the inhibitory effect of the necrotrophic BCA and we show that a loss of fluorescence in parasitised hyphae of GFP-tagged <em>F. graminearum </em>coincides with the detection of GFP in mycelium of <em>C. rosea</em>. The versatility of our device to operate under both water-saturated and nutrient-rich as well as dry and nutrient-deficient conditions, coupled with its spatio-temporal output, opens new opportunities to study relationships between fungi.
DOI: 10.5281/zenodo.3779002
title: SIRAH-CoV2 initiative: S1 Receptor Binding Domain in complex with human antibody CR3022 (PDBid: 6W41)

description: This dataset contains the trajectory of a 12 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV-2 receptor binding domain in complex with a human antibody CR3022 (PDB id: 6W41). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Glycans have been removed from the structures. The file 6W41_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W41_SIRAHcg_12us_prot.tar contains only the protein coordinates, while 6W41_SIRAHcg_12us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W41_SIRAHcg_12us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6w41_SIRAHcg_prot.prmtop 6w41_SIRAHcg_prot.ncrst 6w41_SIRAHcg_prot_12us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3779001
title: SIRAH-CoV2 initiative: S1 Receptor Binding Domain in complex with human antibody CR3022 (PDBid: 6W41)

description: This dataset contains the trajectory of a 12 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV-2 receptor binding domain in complex with a human antibody CR3022 (PDB id: 6W41). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Glycans have been removed from the structures. The file 6W41_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6W41_SIRAHcg_12us_prot.tar contains only the protein coordinates, while 6W41_SIRAHcg_12us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6W41_SIRAHcg_12us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6w41_SIRAHcg_prot.prmtop 6w41_SIRAHcg_prot.ncrst 6w41_SIRAHcg_prot_12us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.5281/zenodo.3803620
title: SIRAH-CoV2 initiative: nsp7-nsp8 complex (PDB id:6YHU)

description: This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 nsp7-nsp8 complex (PDB id: 6YHU, Bioassembly 1). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. The file 6YHU_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com. Additionally, the file 6YHU_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6YHU_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns. To take a quick look at the trajectory: 1- Untar the file 6YHU_SIRAHcg_10us_prot_skip10ns.tar 2- Open the trajectory on VMD using the command line: vmd 6yhu_SIRAHcg_prot.prmtop 6yhu_SIRAHcg_prot.ncrst 6yhu_SIRAHcg_prot_10us_skip10ns.nc -e sirah_vmdtk.tcl Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. This dataset is part of the SIRAH-CoV2 initiative. For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) Sergio Pantano (spantano@pasteur.edu.uy).
description: {"references": ["Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)", "Machado & Pantano JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)", "Machado & Pantano Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)"]}
DOI: 10.15468/dl.anqc4p
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Oenothera biennis L."
 ]
}

 The dataset includes 190 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021740-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive4475.20221219.7.1
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.7397311
title: ARRIVE author checklist

description: ARRIVE author checklist
DOI: 10.13145/bacdive4476.20220920.7
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive4476.20221219.7.1
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive4477.20220920.7
title: Escherichia coli (Migula 1895) Castellani and Chalmers 1919

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.