AndreaBozzo/ceres-open-data-index huggingface dataset:
Stadtbezirke Jugendquotient

Der Jugendquotient gibt den Anteil der unter 20-Jährigen bezogen auf die erwerbsfähigen Personen im Alter von 20 bis 64 Jahren an. Ein Wert von 30 besagt beispielsweise, dass auf 100 potenziell erwerbsfähige Personen 30 Kinder und Jugendliche kommen. Der Indikator gibt Anhaltspunkte, in welchem Umfang der erwerbsfähigen Bevölkerung Versorgungskosten für die jüngere Generation auftreten können. Häufig wird der Quotient als Indikator zur Familienprägung für entsprechende Gebiete verwendet. Referenz des Herausgebers: https://statistik.wuerzburg.de
Stadtbezirke Medianalter

Ziel der Bevölkerungsstatistik ist die Bereitstellung von Auswertungen der melderechtlich registrierten Einwohner am Ort der Hauptwohnung. Zu den melderechtlich registrierten Einwohnern am Ort der Hauptwohnung zählen alle in Würzburg gemeldeten Personen mit Hauptwohnung. Personen, die in Würzburg mehrere Wohnsitze haben, werden nur einmal, und zwar am Ort der Hauptwohnung nachgewiesen. Das Medianalter ist das Lebensalter, das die nach dem Alter geordnete Bevölkerung in zwei gleich große Gruppen teilt: Die Hälfte der Bevölkerung ist jünger als das Medianalter, die andere Hälfte ist älter. Im Gegensatz zum Durchschnittsalter werden beim Medianalter Verzerrungen durch Extremwerte vermieden. Ähnlich wie das Durchschnittsalter liefert auch das Medianalter Hinweise auf Alterungsprozesse in der Bevölkerung. Referenz des Herausgebers: https://statistik.wuerzburg.de
Stadtbezirke Wohnberechtigte

Ziel der Bevölkerungsstatistik ist die Bereitstellung von Auswertungen der melderechtlich registrierten wohnberechtigten Einwohnerinnen und Einwohner. Zu den wohnberechtigten Einwohnerinnen und Einwohnern zählen diejenigen Personen, die in der Stadt Würzburg eine Wohnung haben, unabhängig davon, ob es sich um eine Haupt- oder Nebenwohnung handelt. Referenz des Herausgebers: https://statistik.wuerzburg.de
Stadtbezirke Wohnberechtigte weiblich

Ziel der Bevölkerungsstatistik ist die Bereitstellung von Auswertungen der melderechtlich registrierten wohnberechtigten Einwohnerinnen und Einwohner. Zu den wohnberechtigten Einwohnerinnen und Einwohnern zählen diejenigen Personen, die in der Stadt Würzburg eine Wohnung haben, unabhängig davon, ob es sich um eine Haupt- oder Nebenwohnung handelt. Referenz des Herausgebers: https://statistik.wuerzburg.de
Wohnberechtigte Altersgruppen

Ziel der Bevölkerungsstatistik ist die Bereitstellung von Auswertungen der melderechtlich registrierten wohnberechtigten Einwohnerinnen und Einwohner. Zu den wohnberechtigten Einwohnerinnen und Einwohnern zählen diejenigen Personen, die in der Stadt Würzburg eine Wohnung haben, unabhängig davon, ob es sich um eine Haupt- oder Nebenwohnung handelt. Referenz des Herausgebers: https://statistik.wuerzburg.de
Wohnberechtigte Altersgruppen weiblich

Ziel der Bevölkerungsstatistik ist die Bereitstellung von Auswertungen der melderechtlich registrierten wohnberechtigten Einwohnerinnen. Zu den wohnberechtigten Einwohnerinnen zählen diejenigen Personen, die in der Stadt Würzburg eine Wohnung haben, unabhängig davon, ob es sich um eine Haupt- oder Nebenwohnung handelt. Referenz des Herausgebers: https://statistik.wuerzburg.de
MassiveFold data for target T1295

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. 4080 predictions were generated for the target = 510 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/])
MassiveFold data for target H1233 - T280

[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 H1222 - T266

[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 H1222 - T266

[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 T1269

[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/])
SLA - Points d'apport volontaire

Localisation des points d'apport volontaire sur l'ensemble du territoire de Saint-Louis Agglomération. Plusieurs types de points d'apport existent et peuvent parfois se trouver au même endroit. Ci-dessous, la liste des différents types de points d'apport volontaire selon les déchets acceptés par chacun : * Conteneur à verre * Conteneur à emballage ménager recyclable * Conteneur à ordure ménagère * Conteneur à biodéchet * Conteneur à textile Concernant les autres types de déchets, les jeux de données "Déchetteries et mini-déchetteries" et "Sites de dépôt des déchets verts" sont disponibles sur le portail Open Data. Services référents des données : Service Open Data - 03.89.70.46.67 Service déchets ménagers - 03.89.70.36.63
MassiveFold data for target T1299

[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/])
MassiveFold data for target T1284

[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/])
Points du canevas planimétrique de m2A

Ensemble de points d'appui, matérialisés par un repère sur le terrain, dont les coordonnées planimétriques (X,Y) sont déterminées avec précision dans le système de référence RGF93-CC48. Les altitudes des points ne sont pas définies. Carte des données : [Visualisation - Points du canevas planimétrique de m2A] Les points du canevas planimétrique servent à la réalisation de travaux topographiques dans les rues et les espaces publics. Compte tenu des risques de déplacement des repères, il est indispensable de procéder avant usage à un contrôle de stabilité avec d'autres repères et à un contrôle des cotes du croquis de repérage, lorsque ce dernier existe. Seule la responsabilité de l’utilisateur sera engagée en l’absence de tels contrôles.
MassiveFold data for target T1280

[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/])
MassiveFold data for target T1279

[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/])
MassiveFold data for target T1278

[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/])
MassiveFold data for target T1276

[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/])
MassiveFold data for target T1274

[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/])
MassiveFold data for target T1272 (subunits)

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. Predictions were only generated for the subunits. 8040 predictions were generated for each subunit = 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/])
MassiveFold data for target T1271 (subunits)

[Lien vers la fiche source] MassiveFold data generated for [CASP16], in collaboration with [ CAPRI ]. Predictions were only generated for the subunits. 2680 predictions were generated for each subunit = 335 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/])
MassiveFold data for target T1266

[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/])
MassiveFold data for target T1246

[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/])