cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh051079.07fu
title: SH051079.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh051080.07fu
title: SH051080.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh051081.07fu
title: SH051081.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh051082.07fu
title: SH051082.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh051083.07fu
title: SH051083.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh051084.07fu
title: SH051084.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh051085.07fu
title: SH051085.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15454/4gnnos/oxxuu6
title: bdetm_pra_0010.tab
DOI: 10.15454/4gnnos/t2mc4q
title: readmeDataBDETM.txt

description: description file
DOI: 10.15454/4maai0/2xqefh
title: F7_t2_2018_population-phenotyping_virulents_number_R_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment collected on Cellule and tested on Apache, characterized with the population-phenotyping. Data for the late stage of the 2018 epidemic.
DOI: 10.15454/4maai0/4fk29z
title: F11_t2_2019_population-phenotyping_virulents_number_R_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment, collected on Cellule and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic
DOI: 10.15454/4maai0/5wb6uj
title: F3_t2_2019_field-severity_means.txt

description: Disease severity means per block, treatment, and cultivar used to calculate a proxy for the size of the virulent subpopulations. Data for the late stage of 2019 epidemic
DOI: 10.15454/4maai0/722ent
title: F13_t2_2019_population-phenotyping_virulents_number_S_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment, collected on Apache and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic
DOI: 10.15454/4maai0/8vqsa9
title: F12_t2_2019_population-phenotyping_virulents_number_R_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Cellule and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic
DOI: 10.15454/4maai0/8wh84y
title: F17_Severity_function.R

description: Function used in main script for field data analysis
DOI: 10.15454/4maai0/cmeqsv
title: F14_t2_2019_population-phenotyping_virulents_number_S_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Apache and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic
DOI: 10.15454/4maai0/dl6yw6
title: F10_t2_2018_TabContglobal_virulence.txt

description: Global contingency table with the number of virulent, avirulent, pathogenic and non-pathogenic isolates per block, treatment, and cultivar collected on field at the late stage of 2018 epidemic and tested with the population-phenotyping. Data is used to calculate a proxy for the size of the virulent subpopulations.
DOI: 10.15454/4maai0/eflnag
title: F4_List_of_isolates.tab

description: List and virulence status of the 3035 isolates phenotyped in the greenhouse
DOI: 10.15454/4maai0/evadwp
title: F21_Realpop_function.R

description: The function used in the main script to calculate the proxy for the size of the virulent subpopulations.
DOI: 10.15454/4maai0/fdk90t
title: F8_t2_2018_population-phenotyping_virulents_number_S_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment, collected on Apache and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of 2018 epidemic
DOI: 10.15454/4maai0/fzyjvd
title: F1_Field_disease_severity_rawdata.csv

description: Field disease severity raw data
DOI: 10.15454/4maai0/hif1nu
title: F20_Realpop_analysis.R

description: The main script to calculate the proxy for the size of the virulent subpopulations.
DOI: 10.15454/4maai0/ikl3jf
title: F5_Disease_score_population-phenotyping_rawdata.tab

description: Disease score raw data for the population-phenotyping.
DOI: 10.15454/4maai0/keq1wg
title: F3_t2_2019_field-severity_means.txt

description: Disease severity means per block, treatment, and cultivar used to calculate a proxy for the size of the virulent subpopulations. Data for the late stage of 2019 epidemic.
DOI: 10.15454/4maai0/kn54gf
title: F2_t2_2018_field-severity_means.txt

description: Disease severity means per block, treatment, and cultivar used to calculate a proxy for the size of the virulent subpopulations. Data for the late stage of 2018 epidemic
DOI: 10.15454/4maai0/kq6kvk
title: F12_t2_2019_population-phenotyping_virulents_number_R_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Cellule and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic.
DOI: 10.15454/4maai0/krufxe
title: F10_t2_2018_TabContglobal_virulence.txt

description: Global contingency table with the number of virulent, avirulent, pathogenic and non-pathogenic isolates per block, treatment, and cultivar collected on field at the late stage of 2018 epidemic and tested with the population-phenotyping. Data is used to calculate a proxy for the size of the virulent subpopulations
DOI: 10.15454/4maai0/m5sdgm
title: F14_t2_2019_population-phenotyping_virulents_number_S_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Apache and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic.
DOI: 10.15454/4maai0/nagxzz
title: F19_Virulence_function.R

description: Function used in main script for population-phenotyping data analysis
DOI: 10.15454/4maai0/ngz62z
title: F11_t2_2019_population-phenotyping_virulents_number_R_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment collected on Cellule and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of the 2019 epidemic.
DOI: 10.15454/4maai0/nw2h8e
title: F6_t2_2018_population-phenotyping_virulents_number_R_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment, collected on Cellule and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of 2018 epidemic
DOI: 10.15454/4maai0/ogayyj
title: F16_Severity_analysis.R

description: Main script for field data analysis.
DOI: 10.15454/4maai0/osazd4
title: F1_Field_disease_severity_rawdata.tab

description: Field disease severity raw data.
DOI: 10.15454/4maai0/q2bbfu
title: F17_Severity_function.R

description: Function used in main script for field data analysis.
DOI: 10.15454/4maai0/r1ijir
title: F9_t2_2018_population-phenotyping_virulents_number_S_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Apache and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2018 epidemic
DOI: 10.15454/4maai0/r6aa8q
title: F4_List_of_isolates.tab

description: List and virulence status of the 3035 isolates phenotyped in the greenhouse.
DOI: 10.15454/4maai0/tdiuuj
title: F9_t2_2018_population-phenotyping_virulents_number_S_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Apache and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2018 epidemic.
DOI: 10.15454/4maai0/tjopca
title: F18_Virulence_analysis.R

description: Main script for population-phenotyping data analysis
DOI: 10.15454/4maai0/tl3upr
title: F20_Realpop_analysis.R

description: Main script to calculate the proxy for the size of the virulent subpopulations
DOI: 10.15454/4maai0/ttfho4
title: F15_t2_2019_TabContglobal_virulence.txt.txt

description: Global contingency table with the number of virulent, avirulent, pathogenic and non-pathogenic isolates per block, treatment, and cultivar collected on field at the late stage of 2019 epidemic and tested with the population-phenotyping. Data is used to calculate a proxy for the size of the virulent subpopulations.
DOI: 10.15454/4maai0/ugfj20
title: F8_t2_2018_population-phenotyping_virulents_number_S_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment, collected on Apache and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of 2018 epidemic.
DOI: 10.15454/4maai0/uivfox
title: F5_Disease_score_population-phenotyping_rawdata.tab

description: Disease score raw data for the population-phenotyping
DOI: 10.15454/4maai0/ulehj4
title: F21_Realpop_function.R

description: Function used in main script to calculate the proxy for the size of the virulent subpopulations
DOI: 10.15454/4maai0/urjtuh
title: F18_Virulence_analysis.R

description: Main script for population-phenotyping data analysis.
DOI: 10.15454/4maai0/utfmhy
title: F13_t2_2019_population-phenotyping_virulents_number_S_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment, collected on Apache and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of 2019 epidemic.
DOI: 10.15454/4maai0/vxysry
title: F16_Severity_analysis.R

description: Main script for field data analysis
DOI: 10.15454/4maai0/wjulym
title: F15_t2_2019_TabContglobal_virulence.txt.txt

description: Global contingency table with the number of virulent, avirulent, pathogenic and non-pathogenic isolates per block, treatment, and cultivar collected on field at the late stage of 2019 epidemic and tested with the population-phenotyping. Data is used to calculate a proxy for the size of the virulent subpopulations
DOI: 10.15454/4maai0/x5dvqd
title: README.md

description: :unav
DOI: 10.15454/4maai0/y9ftxo
title: F7_t2_2018_population-phenotyping_virulents_number_R_on_S.txt

description: Contingency table with the number of pathogenic and non-pathogenic isolates per block and treatment, collected on Cellule and tested on Apache, characterized with the population-phenotyping. Data for the late stage of 2018 epidemic
DOI: 10.15454/4maai0/ylczqn
title: F6_t2_2018_population-phenotyping_virulents_number_R_on_R.txt

description: Contingency table with the number of virulent and avirulent isolates per block and treatment collected on Cellule and tested on Cellule, characterized with the population-phenotyping. Data for the late stage of the 2018 epidemic.
DOI: 10.15454/4maai0/ylrgzd
title: F2_t2_2018_field-severity_means.txt

description: Disease severity means per block, treatment, and cultivar used to calculate a proxy for the size of the virulent subpopulations. Data for the late stage of 2018 epidemic.
DOI: 10.15454/4maai0/z5vef5
title: F19_Virulence_function.R

description: Function used in main script for population-phenotyping data analysis.
DOI: 10.15454/4nyhd6/291p3r
title: plasmopara_viticola_INRA-PV221.geneAnnotation.tar.gz

description: Gene annotation of the Plasmopara viticola genome. Includes annotation in gff3 format, a fasta file with protein sequences, and training files for augustus.
DOI: 10.15454/4nyhd6/44zqw8
title: plasmopara_viticola_INRA-PV221.mitochondrion.tar.gz

description: Complete sequence and gene/rRNA/tRNA annotation for the mitochondrion of Plasmopara viticola. NOT described in the MBE paper.
DOI: 10.15454/4nyhd6/hsp7bm
title: plasmopara_viticola_INRA-PV221.assembly.PBv1.fasta.gz

description: Genome assembly of Plasmopara viticola using PacBio long reads at high coverage.
DOI: 10.15454/4nyhd6/i1qsvk
title: plasmopara_viticola_INRA-PV221.repeatAnnotation.tar.gz

description: Annotation of repeat sequences in the genome of Plasmopara viticola. Includes repeat annotation in gff3 format and repeat library in fasta format.
DOI: 10.15454/4nyhd6/rxmwt4
title: plasmopara_viticola_INRA-PV221.mitochondrion.v2.tar.gz

description: Complete sequence and gene/rRNA/tRNA annotation for the mitochondrion of Plasmopara viticola. NOT described in the MBE paper.
DOI: 10.15454/4nyhd6/sgajto
title: plasmopara_viticola_INRA-PV221.functionalAnnot.tar.gz

description: Functional annotation of the Plasmopara viticola proteome. Includes blast2Go results and list of secreted proteins.
DOI: 10.15454/4nyhd6/xgscw8
title: scripts_assembly.tar.gz

description: Scripts used for the removal of redundant scaffolds and for sequence polishing during the genome assembly.
DOI: 10.15454/4rqrig/fzbbwg
title: Composition.txt

description: Composition of fructo-oligosaccharides' solutions
DOI: 10.15454/4rqrig/lbjhyz
title: Physical Characterization.txt

description: Physical properties of fructo-oligosaccharides' solutions and reference compounds
DOI: 10.15454/4sg77p/fcqmq8
title: rpg_complete_2018_d42.zip

description: :unav
DOI: 10.15454/4vvuis/2buzpu
title: Croissance_0-2ans_Vx.tab

description: :unav
DOI: 10.15454/4vvuis/quxn7q
title: Metadonnees_Croissance_0-2ans_Vx.tab

description: :unav
DOI: 10.15454/4w9dm2/05hztr
title: outputmeans2017-10-30 10-37_OD0_B.prn

description: :unav
DOI: 10.15454/4w9dm2/2ieb5h
title: Unifrac_distance_matrix.txt

description: :unav
DOI: 10.15454/4w9dm2/37yvoz
title: outputmeans2017-10-30 09-24 TD1_B.prn

description: :unav
DOI: 10.15454/4w9dm2/4juetd
title: outputmeans2017-10-27 10-41 OD1.prn

description: :unav
DOI: 10.15454/4w9dm2/7t7vlj
title: outputmeans2017-10-26 17-56 FD1.prn

description: :unav
DOI: 10.15454/4w9dm2/9jfkqg
title: outputmeans2017-10-30 09-58_BD0_B.prn

description: :unav
DOI: 10.15454/4w9dm2/a2crnl
title: Correlation IB.csv

description: :unav
DOI: 10.15454/4w9dm2/aymwpk
title: outputmeans2017-10-30 09-43_FD2_B.prn

description: :unav
DOI: 10.6084/m9.figshare.19652568.v1
title: AlphaFold Results: Top predicted model for BM5 antibody sequence with template

description: AlphaFold is used to regenerate the antibody structures in BM5 starting only from the sequence and is only allowed to use templates that pass the similarity thresholds (less than 80% sequence identity) ranked and selected by criteria described in detail in our protocol. This dataset contains the top predicted model from each of the runs before any relaxation. The name of the file is named as follows: "PDBID.of.complex.in.BM5"_"PDBID.of.antibody.template"_unrelaxed_model_0_1.pdb
DOI: 10.15454/4w9dm2/c9gbyn
title: outputmeans2017-10-30 09-38_DD0_B.prn

description: :unav
DOI: 10.6084/m9.figshare.19652568
title: AlphaFold Results: Top predicted model for BM5 antibody sequence with template

description: AlphaFold is used to regenerate the antibody structures in BM5 starting only from the sequence and is only allowed to use templates that pass the similarity thresholds (less than 80% sequence identity) ranked and selected by criteria described in detail in our protocol. This dataset contains the top predicted model from each of the runs before any relaxation. The name of the file is named as follows: "PDBID.of.complex.in.BM5"_"PDBID.of.antibody.template"_unrelaxed_model_0_1.pdb
DOI: 10.15454/4w9dm2/dkkdwv
title: outputmeans2017-10-26 16-52 TD2.prn

description: :unav
DOI: 10.15454/4w9dm2/dwboxs
title: outputmeans2017-10-30 10-38_OD2_B.prn

description: :unav
DOI: 10.15454/4w9dm2/fqukmf
title: Indices_Clean_0.05.txt

description: :unav
DOI: 10.15454/4w9dm2/fum5az
title: outputmeans2017-10-27 10-51 OD2.prn

description: :unav
DOI: 10.15454/4w9dm2/g7z37g
title: outputmeans2017-10-30 09-36_TD2_B.prn

description: :unav
DOI: 10.15454/4w9dm2/guadeb
title: outputmeans2017-10-27 10-37 BD0.prn

description: :unav
DOI: 10.15454/4w9dm2/hexdtw
title: outputmeans2017-10-30 09-40_DD2_B.prn

description: :unav
DOI: 10.15454/4w9dm2/hnle0y
title: outputmeans2017-10-26 10-59 TD0.prn

description: :unav
DOI: 10.15454/4w9dm2/ivmuek
title: outputmeans2017-10-30 09-42_FD1_B.prn

description: :unav
DOI: 10.15454/4w9dm2/jcaebl
title: FiltreredVOCFluxes.tab

description: :unav
DOI: 10.15454/4w9dm2/jxopds
title: outputmeans2017-10-30 09-11 TD0_B.prn

description: :unav
DOI: 10.15454/4w9dm2/klexoj
title: outputmeans2017-10-27 10-39 BD2.prn

description: :unav
DOI: 10.15454/4w9dm2/kyirsm
title: outputmeans2017-10-26 16-44 TD1.prn

description: :unav
DOI: 10.15454/4w9dm2/miufbc
title: outputmeans2017-10-27 10-38 BD1.prn

description: :unav
DOI: 10.15454/4w9dm2/mref9v
title: outputmeans2017-10-26 18-01 FD2.prn

description: :unav
DOI: 10.15454/4w9dm2/nt261s
title: outputmeans2017-10-30 09-39_DD1_B.prn

description: :unav