cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25906249
title: Simulation data for compact ion-pair aggregate electrolyte

description: - AIMDThe AIMD snapshot (in VASP format) for Fig. 5 and Supplementary Fig. 49<br>- cmdThe classical molecular dynamic (cMD) simulation input files (in Gromacs formation for) Fig. 4a-d, Supplementary Fig.33，Fig.34，Fig.36，Fig.41, Fig.45, Fig.46, Supplementary Table 4Fig. 47- pDOSThe snapshot of density functional theory (DFT) pDOS analysis for Supplementary Fig. 47, Supplementary Fig.48<br>The DFT calculations are carried out using VASP 5.4.4.The cMD simulations are carried out using Gromacs 2020.3.
DOI: 10.15468/dl.ke2bvv
title: Occurrence Download

description: A dataset containing 597 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Drimia exuviata (Jacq.) Jessop"
 ]
}

 The dataset includes 597 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026699-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xdrgc5
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Madoqua saltiana (Blainville, 1816)"
 ]
}

 The dataset includes 173 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0070383-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cpwlva
title: Occurrence Download

description: A dataset containing 74602 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Symphoricarpos Duhamel"
 ]
}

 The dataset includes 74602 records from 474 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016420-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.txzv6f
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dolicholobium forbesii Wernham"
 ]
}

 The dataset includes 11 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026707-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ebvajg
title: Occurrence Download

description: A dataset containing 2343 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Figure 9) Range chart of selected dinocysts and acritarchs of ODP Hole 104-644A cores 7-12"
 ]
}

 The dataset includes 2343 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010411-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fssgmc
title: Occurrence Download

description: A dataset containing 3302361 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 2014-2024"
 ]
}

 The dataset includes 3302361 records from 1583 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048339-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5n95c8
title: Occurrence Download

description: A dataset containing 3412245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Geometry POLYGON((-10.45899 39.35459,-8.50309 39.35459,-8.50309 42.6092,-10.45899 42.6092,-10.45899 39.35459))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3412245 records from 659 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015689-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21410/7e4/uq55hb
title: French Election Study 2022, Vague 1 (ELIPSS 2021)

description: Dans la lignée des précédentes éditions de la French election study (FES), le panel FES-2022 représente une contribution à la compréhension des dynamiques électorales pendant la séquence électorale française de 2022 (élection présidentielle an avril et élections législatives au mois de juin). Le projet est collaboratif et comprend cinq vagues d’interrogation en tout, de novembre 2021 à juillet 2022. Il s’inscrit dans la programmation plus générale du panel Elipss. Cette première vague de FES-2022 a été réalisée du 11 novembre au 16 décembre 2021. Elle s’intéresse principalement aux enjeux de la campagne (saillance, compétence des candidats), au suivi et à la perception de la campagne électorale ainsi qu’aux intentions de vote (probabilité d’aller voter, propensions de vote pour les principaux candidats déclarés ou non déclarés). Cette vague comprend également le positionnement des candidats sur l’échelle gauche - droite et l’opinion des répondants sur une série d’enjeux.
DOI: 10.21410/7e4/uq55hb/7qzv5g
title: fr_cdsp_ddi_elipss_202111fes2022.tab

description: :unav
DOI: 10.21410/7e4/uq55hb/8iqfyk
title: fr_cdsp_ddi_elipss_fes2022_V1.sas.zip

description: :unav
DOI: 10.21410/7e4/uq55hb/a1bsih
title: fr_cdsp_ddi_elipss_202111fes2022.xml

description: :unav
DOI: 10.21410/7e4/uq55hb/alqd6j
title: fr_cdsp_ddi_elipss_202112fes22.sas.zip

description: :unav
DOI: 10.21410/7e4/uq55hb/alqzax
title: fr_cdsp_ddi_elipss_fes2022_V1-1.tab

description: :unav
DOI: 10.21410/7e4/uq55hb/avs7dy
title: Questionnaire_fes22_2021_EN.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/cpqwyh
title: fr_cdsp_ddi_elipss_202112fes22-1.tab

description: :unav
DOI: 10.21410/7e4/uq55hb/dwsycl
title: ponderations_elipss_guide.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/faliot
title: fr_cdsp_ddi_elipss_fes2022_V1.csv.zip

description: :unav
DOI: 10.21410/7e4/uq55hb/gqj4f5
title: Documentation_FES2022_V1.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/ixm4e3
title: fr_cdsp_ddi_elipss_202111fes2022.sas.zip

description: :unav
DOI: 10.21410/7e4/uq55hb/ke3lij
title: fr_cdsp_ddi_elipss_fes2022_V1.xml

description: :unav
DOI: 10.21410/7e4/uq55hb/khryek
title: pond2020.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/mckb7x
title: fr_cdsp_ddi_elipss_fes2022_V1.xml

description: :unav
DOI: 10.21410/7e4/uq55hb/orzkib
title: Questionnaire_fes22.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/ozdgkl
title: Questionnaire_FES22_V1.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/q6uwam
title: Documentation_FES22.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/r7thst
title: fr_cdsp_ddi_elipss_202111fes2022-1.tab

description: :unav
DOI: 10.21410/7e4/uq55hb/t7p5pi
title: fr.cdsp.ddi.elipss.202111fes2022.xml

description: :unav
DOI: 10.21410/7e4/uq55hb/tyahxl
title: 201803_ponderations_du_panel_elipss_v1.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/vnozxa
title: fr_cdsp_ddi_elipss_202112fes22.csv.zip

description: :unav
DOI: 10.21410/7e4/uq55hb/xhvibx
title: fr_cdsp_ddi_elipss_fes2022_V1.tab

description: :unav
DOI: 10.21410/7e4/uq55hb/xpo2ss
title: Documentation_FES22.pdf

description: :unav
DOI: 10.21410/7e4/uq55hb/za3u1f
title: fr_cdsp_ddi_elipss_202112fes22.tab

description: :unav
DOI: 10.15468/dl.6hph22
title: Occurrence Download

description: A dataset containing 487 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus houstonensis (Sanders, 1953))"
 ]
}

 The dataset includes 487 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015721-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xfrnf8
title: Occurrence Download

description: A dataset containing 221 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material citation)",
 "Country is Colombia",
 "TaxonKey is Thomisidae"
 ]
}

 The dataset includes 221 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015722-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/bvcb-8p38
title: Unlearnable Data

description: Making images unlearnable through imperceptible perturbations is to prevent unauthorized image scraping from training deep neural networks (DNNs). Most existing methods for breaking these unlearnable data focus on applying image transformation techniques to disrupt the added perturbations, with limited attention given to modifying the classification tasks (target classes) of DNNs as an alternative approach. In this paper, we explore the vulnerabilities of unlearnable data, focusing mainly on modifying the classification tasks rather than applying image transformation techniques. We first experimentally demonstrate that DNNs can learn from unlearnable data by modifying their classification tasks and then propose a divide and conquer framework for breaking unlearnable data. The proposed framework breaks unlearnable data by decomposing a given classification task into simple classification tasks, which is robust to unlearnable data, and performing the given classification task using the simplified tasks. To find the optimal way to decompose the classification task, we propose both a manual approach and an automated approach based on genetic algorithms. We further apply nonlinear transformations to unlearnable data to make the DNNs in our framework more robust to the unlearnable data. After evaluating our framework on breaking six prominent unlearnable CIFAR-10 datasets, we achieve a test accuracy similar to clean data (more than 85%), highlighting the vulnerability of existing unlearnable data. This study shows that existing unlearnable data must be improved in order to prevent DNNs from learning by modifying the classification tasks.
DOI: 10.5281/zenodo.14898461
title: Sawfish Bioinformatics App Note SV VCFs and assessment results

description: This tarball "sawfish_publication_sv_vcfs_and_assessments.tar.gz" contains structural variant VCFs from analyses in the sawfish Bioinformatics App Note, as well as the corresponding VCF assessment results and assessment scripts. The corresponding Bioinformatics article can be found here: https://doi.org/10.1093/bioinformatics/btaf136The top 3 levels of of the tarball file tree are as follows:

sawfish_publication_sv_vcfs_and_assessments
├── CEPH1463_pedigree_analysis
│   ├── assessment_scripts
│   │   ├── ceph.GRCh38.viterbi.oa.csv.gz
│   │   ├── get_gqcut.bash
│   │   ├── get_pass_ge50.bash
│   │   └── run_concordance.bash
│   ├── README.md
│   └── sv_calls
│       ├── pbsv
│       ├── sawfish
│       └── sniffles
├── HG002_depth_titration
│   ├── assessment_scripts
│   │   ├── giab_cmrg
│   │   ├── giab_t2t_20241113
│   │   └── truvari_utils
│   ├── benchmark_data
│   │   ├── cmrg_1.0
│   │   └── T2T_V0.019-20241113_T2T-HG002-Q100v1.1
│   ├── README.md
│   ├── reference_fasta
│   │   ├── human_GRCh38_no_alt_analysis_set.fasta
│   │   ├── human_GRCh38_no_alt_analysis_set.fasta.fai
│   │   └── README.md
│   ├── singuarlity_images
│   │   ├── README.md
│   │   └── truvari-v4.2.2.sif
│   └── sv_calls
│       ├── pbsv
│       ├── sawfish
│       └── sniffles
└── README.md
DOI: 10.5281/zenodo.14898462
title: Sawfish Bioinformatics App Note SV VCFs and assessment results

description: This tarball "sawfish_publication_sv_vcfs_and_assessments.tar.gz" contains structural variant VCFs from analyses in the sawfish Bioinformatics App Note, as well as the corresponding VCF assessment results and assessment scripts. The corresponding Bioinformatics article can be found here: https://doi.org/10.1093/bioinformatics/btaf136The top 3 levels of of the tarball file tree are as follows:

sawfish_publication_sv_vcfs_and_assessments
├── CEPH1463_pedigree_analysis
│   ├── assessment_scripts
│   │   ├── ceph.GRCh38.viterbi.oa.csv.gz
│   │   ├── get_gqcut.bash
│   │   ├── get_pass_ge50.bash
│   │   └── run_concordance.bash
│   ├── README.md
│   └── sv_calls
│       ├── pbsv
│       ├── sawfish
│       └── sniffles
├── HG002_depth_titration
│   ├── assessment_scripts
│   │   ├── giab_cmrg
│   │   ├── giab_t2t_20241113
│   │   └── truvari_utils
│   ├── benchmark_data
│   │   ├── cmrg_1.0
│   │   └── T2T_V0.019-20241113_T2T-HG002-Q100v1.1
│   ├── README.md
│   ├── reference_fasta
│   │   ├── human_GRCh38_no_alt_analysis_set.fasta
│   │   ├── human_GRCh38_no_alt_analysis_set.fasta.fai
│   │   └── README.md
│   ├── singuarlity_images
│   │   ├── README.md
│   │   └── truvari-v4.2.2.sif
│   └── sv_calls
│       ├── pbsv
│       ├── sawfish
│       └── sniffles
└── README.md
DOI: 10.15468/dl.hn2ej6
title: Occurrence Download

description: A dataset containing 3758 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Anaxyrus microscaphus (Cope, 1867))"
 ]
}

 The dataset includes 3758 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015723-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15190947
title: Table 1 in An integrative systematic revision of the wishbone spiders (Araneae: Anamidae: Aname L. Koch, 1873) of subtropical and tropical eastern Australia, with the description of 55 new species

description: Table 1. Name of measurements labelled as numbers in Figure 2, and referenced in species diagnoses and descriptions.
No.Name1Prosoma length (summed with abdomen length to get total body length)2Carapace length3Clypeus to fovea length4Carapace width5Caput width6Fovea width7Eye group length8Eye group width9Abdomen length10Sternum length11Sternum width12Posterior sigilla length13Central sternum to posterior sigilla length14Femur I length15Patella I length16Tibia I length17Metatarsus I length18Tarsus I length19Tibia I length to distal face of spur (TIS sensu Castalanelli et al. 2020)20Tibia I width (TID sensu Castalanelli et al. 2020).21Tibial spur height (TISH sensu Castalanelli et al. 2020).22Tibial megaspine length23Metatarsus I width (MID sensu Castalanelli et al. 2020)24Pedipalp tibia length (PTL sensu Castalanelli et al. 2020)25Asetose depression length (PDL sensu Castalanelli et al. 2020)26Pedipalp tibia width27Cymbium length28Copulatory organ length29Bulb length30Bulb width31Embolus length32Embolus width33Female genitalia width34Lateral vesicle length35Lateral vesicle width36Medial vesicle length37Medial vesicle width
description: Published as part of Wilson, Jeremy D., Harvey, Mark S., Simmons, Leigh W. & Rix, Michael G., 2025, An integrative systematic revision of the wishbone spiders (Araneae: Anamidae: Aname L. Koch, 1873) of subtropical and tropical eastern Australia, with the description of 55 new species, pp. 8 in European Journal of Taxonomy 985 on page 8, DOI: 10.5852/ejt.2025.985.2845, http://zenodo.org/record/15169471
DOI: 10.5281/zenodo.15190948
title: Table 1 in An integrative systematic revision of the wishbone spiders (Araneae: Anamidae: Aname L. Koch, 1873) of subtropical and tropical eastern Australia, with the description of 55 new species

description: Table 1. Name of measurements labelled as numbers in Figure 2, and referenced in species diagnoses and descriptions.
No.Name1Prosoma length (summed with abdomen length to get total body length)2Carapace length3Clypeus to fovea length4Carapace width5Caput width6Fovea width7Eye group length8Eye group width9Abdomen length10Sternum length11Sternum width12Posterior sigilla length13Central sternum to posterior sigilla length14Femur I length15Patella I length16Tibia I length17Metatarsus I length18Tarsus I length19Tibia I length to distal face of spur (TIS sensu Castalanelli et al. 2020)20Tibia I width (TID sensu Castalanelli et al. 2020).21Tibial spur height (TISH sensu Castalanelli et al. 2020).22Tibial megaspine length23Metatarsus I width (MID sensu Castalanelli et al. 2020)24Pedipalp tibia length (PTL sensu Castalanelli et al. 2020)25Asetose depression length (PDL sensu Castalanelli et al. 2020)26Pedipalp tibia width27Cymbium length28Copulatory organ length29Bulb length30Bulb width31Embolus length32Embolus width33Female genitalia width34Lateral vesicle length35Lateral vesicle width36Medial vesicle length37Medial vesicle width
description: Published as part of Wilson, Jeremy D., Harvey, Mark S., Simmons, Leigh W. & Rix, Michael G., 2025, An integrative systematic revision of the wishbone spiders (Araneae: Anamidae: Aname L. Koch, 1873) of subtropical and tropical eastern Australia, with the description of 55 new species, pp. 8 in European Journal of Taxonomy 985 on page 8, DOI: 10.5852/ejt.2025.985.2845, http://zenodo.org/record/15169471
DOI: 10.15468/dl.8qwn42
title: Occurrence Download

description: A dataset containing 11370 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material citation, Material sample, Human Observation)",
 "Country is Nicaragua",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 11370 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015724-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21410/7e4/5v1gow
title: Enquête annuelle - vague 6 (ELIPSS 2018)

description: L’enquête annuelle ELIPSS a pour objectif de disposer de nombreuses variables socio-démographiques, ainsi que de variables de croisement et d’indicateurs fréquemment utilisés en sciences humaines et sociales. Le questionnaire a été construit en collaboration avec plusieurs chercheurs spécialistes des thèmes abordés (cf. "Autres identifications et remerciements"). En outre, les questions retenues sont très largement issues d’enquêtes existantes et une grande partie est répétée chaque année. L’enquête annuelle traite les questions suivantes : - état civil du panéliste ; - travail et formation ; - description socio-démographique du ménage ; - logement et quartier ; - revenus et patrimoine ; - liens sociaux ; - pratiques de loisirs, pratiques culturelles ; - croyances et pratiques religieuses ; - comportements et opinions politiques ; - état et comportement de santé ; - habitudes de vie. The purpose of the ELIPSS Annual survey is to obtain numerous sociodemographic variables, together with interactive variables and indicators frequently used in the social sciences. The questionnaire was constructed in collaboration with several researchers specialising in the topics concerned. In addition, the questions used are extensively based on existing surveys and many of them are repeated every year. The Annual Survey tackles the following questions: the panellist’s civil status, work and education, sociodemographic description of the household, home and neighbourhood, income and assets, social ties, leisure practices, cultural practices, religious beliefs and practices, political behaviours and opinions, health condition and behaviour, lifestyle.
DOI: 10.21410/7e4/5v1gow/4dlrlb
title: fr_cdsp_ddi_elipss_201803ea.tab

description: :unav
DOI: 10.21410/7e4/5v1gow/6lgwq1
title: 201803_ponderations_du_panel_elipss_v1.pdf

description: :unav
DOI: 10.21410/7e4/5v1gow/7r1xy2
title: fr.cdsp.ddi.elipss.201903.ea.csv.zip

description: :unav
DOI: 10.21410/7e4/5v1gow/dgxt7d
title: fr_cdsp_ddi_elipss_201803ea.dta.zip

description: :unav
DOI: 10.21410/7e4/5v1gow/ffptps
title: Documentation_EA2018.pdf

description: :unav
DOI: 10.21410/7e4/5v1gow/fxf2fw
title: fr.cdsp.ddi.elipss.201903.ea.sas.zip

description: :unav
DOI: 10.21410/7e4/5v1gow/gtq7b6
title: Documentation_EA2018.xml

description: :unav
DOI: 10.21410/7e4/5v1gow/jdcbsw
title: fr_cdsp_ddi_elipss_201803ea.csv.zip

description: :unav
DOI: 10.21410/7e4/5v1gow/kxq8at
title: fr_cdsp_ddi_elipss_201803ea.sas.zip

description: :unav
DOI: 10.21410/7e4/5v1gow/kzfcyp
title: Documentation_EA2018.xml.xml

description: :unav
DOI: 10.21410/7e4/5v1gow/ofgj5e
title: Questionnaire_EA2019.pdf

description: :unav
DOI: 10.21410/7e4/5v1gow/roucm7
title: fr.cdsp.ddi.elipss.201903.ea.tab

description: :unav
DOI: 10.21410/7e4/5v1gow/uskebd
title: fr.cdsp.ddi.elipss.201903.ea.stata.zip

description: :unav
DOI: 10.21410/7e4/5v1gow/uuepgo
title: Documentation_EA2019.xml

description: :unav
DOI: 10.21410/7e4/5v1gow/x2qz4m
title: Questionnaire_EA2018.pdf

description: :unav
DOI: 10.21410/7e4/5v1gow/y49owo
title: Documentation_EA2019.pdf

description: :unav
DOI: 10.5281/zenodo.14825950
title: Mass spectrometry and NMR data for comparative metabolomics of Phakellia ventilabrum

description: Mass spectrometry and NMR data collected from crude and partially purified extracts from the deep-sea sponge Phakellia ventilabrum. Mzxml converted spectra and Mzmine batch file for data processing. HPCA-F were collected using a Bruker MAXIS II Q-ToF mass spectrometer, coupled to an Agilent 1290 UHPLC. HPC85/b were collected using a ThermoScientific Orbitrap IQ-X MS connected to Thermo Instruments UPLC system. NMR spectra were recorded on a Bruker AVANCE III spectrometer (Thermo Fisher Scientific, Geel, Belgium) at 400 MHz for 24 cycles with H2O suppression.
DOI: 10.5281/zenodo.15188722
title: Mass spectrometry and NMR data for comparative metabolomics of Phakellia ventilabrum

description: Mass spectrometry and NMR data collected from crude and partially purified extracts from the deep-sea sponge Phakellia ventilabrum. Mzxml converted spectra and Mzmine batch file for data processing. HPCA-F were collected using a Bruker MAXIS II Q-ToF mass spectrometer, coupled to an Agilent 1290 UHPLC. HPC85/b and Phakellia HCD were collected using a ThermoScientific Orbitrap IQ-X MS connected to Thermo Instruments UPLC system. NMR spectra were recorded on a Bruker AVANCE III spectrometer (Thermo Fisher Scientific, Geel, Belgium) at 400 MHz for 24 cycles with H2O suppression.
DOI: 10.5281/zenodo.14825949
title: Mass spectrometry and NMR data for comparative metabolomics of Phakellia ventilabrum

description: Mass spectrometry and NMR data collected from crude and partially purified extracts from the deep-sea sponge Phakellia ventilabrum. Mzxml converted spectra and Mzmine batch file for data processing. HPCA-F were collected using a Bruker MAXIS II Q-ToF mass spectrometer, coupled to an Agilent 1290 UHPLC. HPC85/b/b1 and Phakellia HCD were collected using a ThermoScientific Orbitrap IQ-X MS connected to Thermo Instruments UPLC system. NMR spectra were recorded on a Bruker AVANCE III spectrometer (Thermo Fisher Scientific, Geel, Belgium) at 400 MHz for 24 cycles with H2O suppression.
DOI: 10.5281/zenodo.15191076
title: Mass spectrometry and NMR data for comparative metabolomics of Phakellia ventilabrum

description: Mass spectrometry and NMR data collected from crude and partially purified extracts from the deep-sea sponge Phakellia ventilabrum. Mzxml converted spectra and Mzmine batch file for data processing. HPCA-F were collected using a Bruker MAXIS II Q-ToF mass spectrometer, coupled to an Agilent 1290 UHPLC. HPC85/b/b1 and Phakellia HCD were collected using a ThermoScientific Orbitrap IQ-X MS connected to Thermo Instruments UPLC system. NMR spectra were recorded on a Bruker AVANCE III spectrometer (Thermo Fisher Scientific, Geel, Belgium) at 400 MHz for 24 cycles with H2O suppression.