cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22002/m1ckk-8ch80
title: V. cholerae CK2188 delta-tcpR

description: Classical strain with ctxA deletionStrain name CK2188 (tcpR gene knonkout)Cell harbors pMT5 plasmid (inducible toxT)
description: <strong>Tilt Series Date:</strong> 2016-08-06</p>
<strong>Data Taken By:</strong> Yi-Wei Chang</p>
<strong>Species / Specimen:</strong> Vibrio cholerae</p>
<strong>Strain:</strong> O395-N1</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1.0°, constant angular increment, dosage: 140.0 eV/Å²,  defocus: -6.0 μm,  magnification: 27500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain from Gabriela Kovacikova</p>
<strong>Purification / Growth Conditions / Treatment:</strong> O/N cultures of Vibrio cholerae O395 N1 pMT5 grown in LB, 1 mM IPTG and 100 ug/mL ampicillin.</p>
<strong>Sample Preparation:</strong> Vitrobot (MK iv) settings: 100% humidity, 3.5µl sample, 10 mg/ml BSA treated gold. Blot force 6, blot time 3 sec. Wait time 0 sec. Drain time 1 sec. Ethane/propane mix. Grid: Quantifoil Cu 2/2 200.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2016-08-06-12/rawdata/</p>20160806_YWC218_10012.mrc,  Tilt Series (Pixel Size 0.39 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2016-08-06-12/rawdata/20160806_YWC218_10012.mrc"
        > <i class="download icon"></i> Download </a></p>

        20160806_YWC218_10012_full.rec,  Reconstruction (Pixel Size 1.56 nm), 534.5 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2016-08-06-12/3dimage_76405/20160806_YWC218_10012_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/sn8mv-js397
title: Coxiella_ Verocells_28dpi

description: Coxiella burnetii Nine Mile phase II clone 4 (NMIIC4) strain. Coxiella cells purified from infected Vero cells.
description: <strong>Tilt Series Date:</strong> 2017-10-19</p>
<strong>Data Taken By:</strong> Debnath Ghosal</p>
<strong>Species / Specimen:</strong> Coxiella burnetii</p>
<strong>Strain:</strong> Nine Mile phase II clone 4</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 2°, constant angular increment, dosage: 130.0 eV/Å²,  defocus: -7.0 μm,  magnification: 27500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain sent to us by Robert Heinzen. Data collected and processed by Debnath Ghosal and Mohammed Kaplan using Caltech tomography pipeline.</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Refer to Heinzen lab.</p>
<strong>Sample Preparation:</strong> Freezing: 100% humidity, 4µl sample, Blot force 6, blot time 4 sec. Wait time 0 sec. Drain time 1 sec. Ethane/propane mix. Grid: Quantifoil Cu 2/2 200. Add gold to cells prior to freezing: 1ul of gold to 4 ul of cells, freeze.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-10-19-10/rawdata/</p>Cb_vero_201710190008.mrc,  Tilt Series (Pixel Size 0.39 nm), 1.7 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-10-19-10/rawdata/Cb_vero_201710190008.mrc"
        > <i class="download icon"></i> Download </a></p>

        Cb_vero_201710190008.rec,  Reconstruction (Pixel Size 1.56 nm), 889.0 MB  
        
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        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/9y1ba-jkw30
title: Lp02 ΔlspDE

description: Raw data files of Lp02 ΔlspDE
description: <strong>Tilt Series Date:</strong> 2017-03-02</p>
<strong>Data Taken By:</strong> Debnath Ghosal</p>
<strong>Species / Specimen:</strong> Legionella pneumophila</p>
<strong>Strain:</strong> Philadelphia-1_Lp02</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1.5°, constant angular increment, dosage: 100.0 eV/Å²,  defocus: -8.0 μm,  magnification: 27500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain sent to us by Nicholas Cianciotto at Northwestern University Medical School Data collected and processed by Debnath Ghosal</p>
<strong>Sample Preparation:</strong> 4 grids were frozen for this strain at OD= 3 Vitrobot (MK iv) settings: 100% humidity, 4µl sample, Blot force 6, blot time 3 sec. Wait time 0 sec. Drain time 1 sec. Ethane/propane mix. Grid: Quantifoil Cu 2/2 200. Add gold to cells prior to freezing: 1ul of gold to 4 ul of cells, freeze.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-03-02-70/rawdata/</p>Lg_DeltaDE_201703020031.mrc,  Tilt Series (Pixel Size 0.39 nm), 2.3 GB  
        
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        > <i class="download icon"></i> Download </a></p>

        Lg_DeltaDE_201703020031_part81_4.rec,  Reconstruction (Pixel Size 1.56 nm), 445.4 MB  
        
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DOI: 10.22002/kz8kr-n5596
title: Xanthomonas vs Caulobacter

description: Xac WT pBRaφ pBRR MCS5 GFP (code 9) vs Caulobacter competition
description: <strong>Tilt Series Date:</strong> 2017-03-30</p>
<strong>Data Taken By:</strong> Debnath Ghosal</p>
<strong>Species / Specimen:</strong> Xanthomonas citri</p>
<strong>Strain:</strong> pv citri 306</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-50.0°, 50.0°), step: 1.5°, constant angular increment, dosage: 160.0 eV/Å²,  defocus: -8.0 μm,  magnification: 27500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Chuck Farah lab made the strains, data collected by Debnath Ghosal.</p>
<strong>Purification / Growth Conditions / Treatment:</strong> 4 µL mixture of Xac and Caulobacter cells were pipetted on top of Au-Finder grids. These grids were glow discharged in advance and kept on top of Agar pads. Carbon side up. These were then kept at the BSL-II hood and left for about 10 min before freezing.</p>
<strong>Sample Preparation:</strong> Freezing conditions: Blot force 6, wait time=0, drain time =1 sec, blot time= 10 sec</p>
description: Files available via S3 at ps://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-03-30-44/rawdata/</p>Xac_Cc_201703295tha0002.mrc,  Tilt Series (Pixel Size 0.39 nm), 1.0 GB  
        
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        Xac_Cc_201703295tha0002.rec,  Reconstruction (Pixel Size 1.56 nm), 890.9 MB  
        
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        > <i class="download icon"></i> Download </a></p>
DOI: 10.15468/dl.che9x5
title: Occurrence Download

description: A dataset containing 107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Livistona mariae F.Muell."
 ]
}

 The dataset includes 107 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009186-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29178401
title: Figure2b.dat

description: Climate change attribution study.
DOI: 10.6084/m9.figshare.29178401.v1
title: Figure2b.dat

description: Climate change attribution study.
DOI: 10.17877/tudodata-2025-mct46naq
title: CHIPMUNK
title: A Virtual Synthesizable Small-Molecule Library for Medicinal Chemistry, Exploitable for Protein-Protein Interaction Modulators

description: &lt;p&gt;
CHIPMUNK is a library containing 95 million molecules derived from in silico reactions.
&lt;/p&gt;

&lt;p&gt;
A common issue during drug design and development is the discovery of novel scaffolds for protein targets. On the one hand the chemical space of purchasable compounds is rather limited; on the other hand artificially generated molecules suffer from a grave lack of accessibility in practice. Therefore, we generated a novel virtual library of small molecules which are synthesizable from purchasable educts, called CHIPMUNK (CHemically feasible In silico Public Molecular UNiverse Knowledge base). Altogether, CHIPMUNK covers over 95 million compounds and encompasses regions of the chemical space that are not covered by existing databases. The coverage of CHIPMUNK exceeds the chemical space spanned by the Lipinski rule of five to foster the exploration of novel and difficult target classes. The analysis of the generated property space reveals that CHIPMUNK is well suited for the design of protein–protein interaction inhibitors (PPIIs). Furthermore, a recently developed structural clustering algorithm (StruClus) for big data was used to partition the sub-libraries into meaningful subsets and assist scientists to process the large amount of data. These clustered subsets also contain the target space based on ChEMBL data which was included during clustering.
&lt;/p&gt;
DOI: 10.15468/dl.fycaen
title: Occurrence Download

description: A dataset containing 627 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scolytus multistriatus",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 627 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019764-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18297810
title: ARG
DOI: 10.5281/zenodo.18297811
title: ARG
DOI: 10.15468/dl.wurzm6
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nyctiophylax hjangsanchonus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019765-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14545193
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.15468/dl.v45kcv
title: Occurrence Download

description: A dataset containing 2627 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Country is one of (United States of America, Canada)",
 "Geometry POLYGON((-106.76336 31.79207,-106.00778 26.50607,-63.4315 15.81959,-62.49855 48.89678,-106.51666 53.64632,-106.76336 31.79207))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Coordinate reprojected, Country coordinate mismatch, Country mismatch, Country invalid, Country derived from coordinates, Continent coordinate mismatch, Continent country mismatch, Continent invalid, Continent derived from country, Continent derived from coordinates, Recorded date mismatch, Recorded date invalid, Recorded date unlikely, Depth not metric, Depth unlikely, Depth min max swapped, Depth non numeric, Elevation unlikely, Elevation min max swapped, Elevation not metric, Elevation non numeric, Modified date invalid, Modified date unlikely, Identified date unlikely, Identified date invalid, Basis of record invalid, Type status invalid, Multimedia date invalid, Multimedia URI invalid, References URI invalid, Error during interpretation, Individual count invalid, Individual count conflicts with occurrence status, Occurrence status unparsable, Occurrence status inferred from individual count, Occurrence status inferred from basis of record, Georeferenced date unlikely, Georeferenced date invalid, Ambiguous institution, Ambiguous collection, Institution match none, Collection match none, Institution match fuzzy, Collection match fuzzy, Institution collection mismatch, Possibly on loan, Different owner institution)",
 "TaxonKey is Vitis aestivalis"
 ]
}

 The dataset includes 2627 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019766-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kfzmta
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Agrostis canina formosana"
 ]
}

 The dataset includes 71 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019767-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18150/cpv165
title: Energy intensity of the polish agri-food sector in the light of input-output tables

description: The dataset covers the agri-food sector in Poland for the years 2014-2019, including agriculture, the food industry, agricultural supply, food industry supply, and agribusiness. Additionally, for comparison purposes, data on the entire economy has also been included.The dataset contains information on final energy consumption, categorized into six groups of energy sources within each analyzed sector, allowing for an assessment of the energy use structure. Moreover, it includes GDP values in Purchasing Power Standard (PPS) for each sector, enabling an analysis of their contribution to economic development.A key component of the dataset is energy intensity indicators, which quantify the amount of energy consumed per unit of GDP (MJ/EUR). These indicators facilitate the assessment of energy intensity across individual sectors and their comparison against the entire economy.Data contains a ReadMe.txt file.
DOI: 10.23729/23c53d54-5c10-4219-8ed2-ebb57c6a56e5
title: JYFL-ACCLAB-JR164 Prompt and delayed spectroscopy of N = 120 nuclei 207Fr and 209Ac
title: JYFL-ACCLAB-JR164 Prompt and delayed spectroscopy of N = 120 nuclei 207Fr and 209Ac

description: Objectives(less than 250 words): Detect and identify the low-lying excited states and possible isomeric states of N = 120 nuclei 207Fr, 209Ac. 176Yb(37Cl,6n)207Fr, until monday and 180Hg(35Cl,6n)209Ac after that.

Achievements (less than 250 words): Experiment was very successful. We managed to collect sufficient amount of statistics for both nuclei. We collected enough 207Fr data for gamma gamma, even gamma-gamma-gamma cube analysis. Similarly, the 209Ac was collected successfully, 3400 recoil-correlated alpha decays were collected, which is sufficient for recoil-decay tagged gamma-ray singles spectrum. In the Ac data there is a previously unknown isomer state, which we do have some idea where it comes from.
DOI: 10.15468/dl.cwmz7c
title: Occurrence Download

description: A dataset containing 487 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Senecio madagascariensis",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 487 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019768-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18150/xykrkc
title: Final energy consumption mix structures in EU agriculture, agribusiness and the total economy (2014–2022) with NECP 2030 targets, monotonicity and attainment-year projections

description: [ENG:]The dataset covers energy consumption structures in agriculture, agribusiness, and the overall economy in European Union countries for the years 2014–2022. The data were developed for 18 EU countries (scenario 1) and 22 EU countries (scenario 2). The spatial scope of the dataset covers the European Union area. The dataset contains information on final energy consumption structures broken down into six energy sources, in line with the classification used in the National Energy and Climate Plans (NECPs). In addition to observed data, the dataset also includes target energy consumption structures for 2030, derived from NECP documents, as well as estimated and scaled energy structures determined on the basis of targets for the share of renewable energy sources (RES).A key component of the dataset consists of projections of the years in which the target energy consumption structure will be achieved, estimated using two distance-based methods: Euclidean and Manhattan, based on the dynamics of changes in energy structures over the periods 2014–2022 and 2018–2022. In addition, the dataset includes a monotonicity indicator (Monotonicity_Level_(η)), which enables an assessment of the consistency and directionality of structural changes over time. The data were developed using an input-output method that integrates economic and energy information, allowing analysis of both direct and indirect energy consumption in agriculture, agribusiness, and the overall economy.
DOI: 10.5281/zenodo.18297398
title: V2V-SynTrust Dataset: Anomaly Detection Dataset for Secure Vehicular Communication in Intelligent Transportation Systems

description: This dataset contains vehicle-to-vehicle communication records for anomaly detection research. The dataset comprises vehicle identifiers and timestamps to preserve vehicle-wise temporal continuity and support leakage-proof data splits. Kinematic and spatial behaviour is captured through speed, acceleration, and GPS coordinates, which evolve continuously over time under physical constraints and may be perturbed during location-based attacks. Communication characteristics are represented by message type, message transmission frequency, packet loss rate, and received signal strength, reflecting both normal and adversarial network conditions. In addition, a synthetically generated trust score is included to emulate the output of a generic trust management mechanism and is manipulated under trust-related attacks. Each record is labelled with a multi-class attack category and a binary malicious indicator, supporting both fine-grained attack classification and binary anomaly detection. The dataset contains 50,000 samples for 17 classes, benign traffic and several attack scenarios, and has a binary labelling scheme which differentiates benign and malicious messages. Instead of being based on unconstrained random value generation, all features are generated according to predefined rules and physical constraints. These constraints provide temporal continuity for vehicle-wise, keeping feasible coupling speed, acceleration, and GPS trajectory, or perturbing thunderstorm, only for communication-and-trust-specific attributes.
DOI: 10.5281/zenodo.18297399
title: V2V-SynTrust Dataset: Anomaly Detection Dataset for Secure Vehicular Communication in Intelligent Transportation Systems

description: This dataset contains vehicle-to-vehicle communication records for anomaly detection research. The dataset comprises vehicle identifiers and timestamps to preserve vehicle-wise temporal continuity and support leakage-proof data splits. Kinematic and spatial behaviour is captured through speed, acceleration, and GPS coordinates, which evolve continuously over time under physical constraints and may be perturbed during location-based attacks. Communication characteristics are represented by message type, message transmission frequency, packet loss rate, and received signal strength, reflecting both normal and adversarial network conditions. In addition, a synthetically generated trust score is included to emulate the output of a generic trust management mechanism and is manipulated under trust-related attacks. Each record is labelled with a multi-class attack category and a binary malicious indicator, supporting both fine-grained attack classification and binary anomaly detection. The dataset contains 50,000 samples for 17 classes, benign traffic and several attack scenarios, and has a binary labelling scheme which differentiates benign and malicious messages. Instead of being based on unconstrained random value generation, all features are generated according to predefined rules and physical constraints. These constraints provide temporal continuity for vehicle-wise, keeping feasible coupling speed, acceleration, and GPS trajectory, or perturbing thunderstorm, only for communication-and-trust-specific attributes.
DOI: 10.5281/zenodo.18297834
title: Pontederia ovalis Mart. ex Schult. & Schult.f. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18297835
title: Pontederia ovalis Mart. ex Schult. & Schult.f. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.15468/dl.5ny9jt
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plectrocnemia baculifera",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 27 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019769-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18297845
title: Pontederia rotundifolia L.f. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18297846
title: Pontederia rotundifolia L.f. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53