AndreaBozzo/ceres-open-data-index huggingface dataset:
MassiveFold data for target H1245 - T296

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target H1244 - T294

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment of MassiveFold predictions for the target. The `chains` column that gives the chains involved in the interface was filled a posteriori from CAPRI generated files and is provided without any warranty. - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target H1244 - T294

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target H1236 - T292

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target H1236 - T292

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment of MassiveFold predictions for the target. The `chains` column that gives the chains involved in the interface was filled a posteriori from CAPRI generated files and is provided without any warranty. - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target T1235 - T290

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target T1235 - T290

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment of MassiveFold predictions for the target. The `chains` column that gives the chains involved in the interface was filled a posteriori from CAPRI generated files and is provided without any warranty. - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
Chemical, physico-chemical quality monitoring of surface waters in the Brussels-Capital Region

Chemical, physico-chemical quality monitoring of surface waters in the Brussels-Capital Region Location of the different surface water quality monitoring sites under the Water Framework Ordonnance and Directive. Surface waters concerned are surface water bodies: Canal, Senne and Woluwe. Monitoring involves a series of chemical, physico-chemical parameters... The code and the name of the monitoring site are given. More info: [https://environnement.brussels/pro/outils-et-donnees/sites-web-et-outils/bruwater-donnees-sur-les-eaux-de-surface-et-les-eaux-souterraines-en-region-bruxelloise] [https://hydria.be/fr/flowbru-fr/] [ ]
Biological quality monitoring of surface waters in the Brussels-Capital Region

Biological quality monitoring of surface waters in the Brussels-Capital Region Location of the different surface water biological quality monitoring sites under the Water Framework Ordonnance and Directive. Surface waters concerned are surface water bodies: Canal, Senne and Woluwe. Monitoring involves a series of biological parameters. More info: [https://environnement.brussels/pro/outils-et-donnees/sites-web-et-outils/bruwater-donnees-sur-les-eaux-de-surface-et-les-eaux-souterraines-en-region-bruxelloise] [https://hydria.be/fr/flowbru-fr/] [ ]
Groundwater level monitoring in the Brussels-Capital Region

Groundwater level monitoring in the Brussels-Capital Region Location of the different groundwater level monitoring sites (or piezometric sites) managed by Brussels Environment under the surveillance monitoring of the groundwater status in accordance with the Ordonnance and the Water Framework Directive. Indication of the analyzed water body, the European Code and the Brussels code of the monitoring site. More info: [https://environnement.brussels/pro/outils-et-donnees/sites-web-et-outils/bruwater-donnees-sur-les-eaux-de-surface-et-les-eaux-souterraines-en-region-bruxelloise] [https://hydria.be/fr/flowbru-fr/] [ ]
RPG complété 2023 Région Centre - Val de Loire

[Lien vers la fiche source] RPG complété 2023. Complète le RPG campagne 2023 pour les départements de la région Centre-Val de Loire (18, 28, 36, 37, 41 et 45 ; combinés). (contient les parcelles agricoles hors RPG) Données géographiques (vectorielles, shapefile), parcellaires. Sources : IGN, OSO/Cesbio. Traitements : INRAE US ODR.
Groundwater quality monitoring in the Brussels-Capital Region

Groundwater quality monitoring in the Brussels-Capital Region Location of the different groundwater quality monitoring sites managed by Brussels Environment and which results are transmitted through the reporting to Europe (under Article 8 of the Water Framework Directive). Indication of the analyzed water body, the European Code and the Brussels code of the monitoring site. Distinction between two types of monitoring: surveillance monitoring for all groundwater bodies (type_monitoring = 1) and operational monitoring for groundwater bodies identified as being at risk of failing to achieve the objectives of good status (type_monitoring = 2). More info: [https://environnement.brussels/pro/outils-et-donnees/sites-web-et-outils/bruwater-donnees-sur-les-eaux-de-surface-et-les-eaux-souterraines-en-region-bruxelloise] [https://hydria.be/fr/flowbru-fr/] [ ]
Collection points / Recypark container parks (Brussels-Capital Region)

Avant toute venue au Recypark, il est essentiel de trier les déchets que vous apporterez. Les Recyparks sont ouverts 7/7, à l’exception des jours fériés. Plus d’info et heures d’ouverture : [https://arp-gan.be/fr/recypark]
Classes des écoles publiques, par degré d'enseignement, par commune, en octobre dès 2010

Ce jeu de données présente le nombre de classes des écoles publiques du canton de Fribourg, ventilé selon le degré d'enseignement, le district et la commune, dès 2010. Les degrés d'enseignement correspondent à la classification suisse de niveau 2 (Degré primaire 1-2, Degré primaire 3-8, Degré secondaire I) pour la scolarité obligatoire. Les effectifs correspondent au nombre de classes recensées en octobre de chaque année. Pour plus d'informations sur la Statistique des élèves et des étudiants (SDL) : [https://www.bfs.admin.ch/bfs/fr/home/statistiques/education-science/enquetes/sdl.assetdetail.35956347.html]
Elèves, par degré d'enseignement (dénombrés au domicile), par commune, dès 2010

Ce jeu de données présente le nombre d'élèves domiciliés dans le canton de Fribourg, ventilé par degrés d'enseignement selon les classifications suisses de niveau 1 et 2, le district et la commune de domicile, dès 2010. Les effectifs correspondent au nombre d'élèves recensés au domicile, indépendamment du canton où se situe l'établissement fréquenté, lors du relevé annuel d'octobre. La Statistique des élèves et des étudiants (SDL) couvre les élèves et étudiants des degrés primaire, secondaire I, secondaire II et des formations professionnelles supérieures du degré tertiaire. Pour plus d'informations sur la Statistique des élèves et des étudiants (SDL): [https://www.bfs.admin.ch/bfs/fr/home/statistiques/education-science/enquetes/sdl.assetdetail.35956347.html]
Elèves, par degré d'enseignement (dénombrés au lieu d'école), par commune, dès 2010

Ce jeu de données présente le nombre d'élèves scolarisés dans le canton de Fribourg, ventilé par degrés d'enseignement selon les classifications suisses de niveau 1 et 2, le district et la commune de l'école, dès 2010. Les effectifs correspondent au nombre d'élèves recensés au lieu d'école, indépendamment du canton ou pays où se situe le domicile de l'élève, lors du relevé annuel d'octobre. La Statistique des élèves et des étudiants (SDL) couvre les élèves et étudiants des degrés primaire, secondaire I, secondaire II et des formations professionnelles supérieures du degré tertiaire. Pour plus d'informations sur la Statistique des élèves et des étudiants (SDL): [https://www.bfs.admin.ch/bfs/fr/home/statistiques/education-science/enquetes/sdl.assetdetail.35956347.html]
19330360-c46a-4bc0-a2cf-9bed1d7cb521

[Lien vers la fiche source] Produit altimétrique combiné Ssalto/Duacs en version DT2021. La longue série de données altimétriques acquise depuis le lancement de Topex/Poséidon en 1992 permet un recul suffisant pour calculer des moyennes statistiques basées sur plusieurs périodes de temps. Les climatologies sont créees à partir des grilles Ssalto/Duacs quotidiennes, temps différé, combinées, basées sur les meilleures échantillonnages disponibles (i.e. série "all sat merged"). Ces produits sont calculés par rapport à une moyenne sur 20 ans (1993-2012), incluant la variabilité saisonnière (aucun cycle n'est retiré). Les variables disponibles sont les suivantes : EKE (Eddy Kinetic Energy) MSLA-H (Sea Level Anomaly H, sea surface height above sea level) MSLA-U (Sea Level Anomaly U, surface geostrophic eastward sea water velocity assuming sea level for_geoid) MSLA-V (Sea Level Anomaly V, surface geostrophic northward sea water velocity assuming sea level for geoid) MADT-H (Absolute Dynamics Topography H : sea surface height above geoid) MADT-U (Absolute Dynamics Topography U, surface geostrophic eastward sea water velocity) MADT-V (Absolute Dynamics Topography V, surface geostrophic northward sea water velocity) Trois types de datasets sont proposées : - Les **moyennes mensuelles** des MSLA sont calculées à partir des cartes d'anomalies de hauteurs de mer, Ssalto/Duacs quotidiennes, temps différé, en moyennant les données sur un même mois, basées sur la période de janvier 1993 jusqu'à août 2023. Il en résulte un fichier et une carte par mois pour chaque année (368 fichiers). - Les **climatologies saisonnières** des MSLA sont calculées à partir des cartes d'anomalies de hauteurs de mer, Ssalto/Duacs quotidiennes, temps différé, moyennées saison par saison (JFM - AMJ - JAS- OND) sur toutes les années. Il en résulte un fichier et une carte par saison (4 fichiers) - Les **climatologies mensuelles** des MSLA sont calculées à partir des cartes d'anomalies de hauteurs de mer, Ssalto/Duacs quotidiennes, temps différé, en moyennant les données sur un même mois, basées sur la période de janvier 1993 jusqu'à fin 2022. Il en résulte un fichier et une carte par mois (12 fichiers)
Profondeur de l'échantillon (m), COT (% ), TN (ppm), COT/TN, δ13Corg (‰ VPDB) et δ15Nbulk (‰ VAIR), pour les échantillons analysés le long des carottes de forage GT13 et GT16 (Formation Serra Sul, Craton amazonien, Brésil)

[Lien vers la fiche source] Nitrogen and Carbon isotope data from the Neoarchean GT13 and GT16 drill cores (Serra Sul Formation, Amazonian Craton, Brazil)
Analyses géochimiques des carbonates pléistocènes des lacs Pyramid et Winnemucca, USA

[Lien vers la fiche source] Geochemical analysis of pleistocene lacustrine carbonates from Pyramid ans Winnemucca Lake, USA. Samples are Columns and Complex domes' pipes, thinolites, and microbialites. This dataset contain bulk elementary analysis of major and traces and total sulfur by ICP-MS and carbon and oxygen stable isotops of carbonates (δ13Ccarb and δ18Ocarb).
Reserved parking spaces registered by Brussels Mobility (City of Brussels)

List of reserved parking spaces registered by Brussels Mobility and located on the territory of the City of Brussels Types: delivery, HGVs, coaches, PRMs, taxis, CDs, police, motorbikes, bicycles, kiss and ride More info: [https://data.mobility.brussels/fr/info/1e898290-d1a0-49c9-8b45-5c08c04f25e7/]
MassiveFold data for target T1234 - T288

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target T1240 - T286

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
MassiveFold data for target T1237 - T282

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from [https://predictioncenter.org/]) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from [https://www.capri-docking.org/assessment/]) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.