cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.71486/fna8-4y35
title:  Dataset of the paper “Grouping products for the optimization of production processes: A case in the steel manufacturing industry”. European Journal of Operational Research, 286(1), 190-202

description: The optimization of a production process is often based on the efficient utilization of the production facility and equipment. In particular, reducing the time to change from producing one product to another is critical to the fulfillment of demand at a minimum cost. We study the production of steel coils in the context of searching for groups of products with similar characteristics in order to create production batches that minimize the cost of fulfilling production orders originated by a known demand. We formulate the problem as mixed-integer program and develop a heuristic solution procedure. We show that a simplified version of the problem is equivalent to the clique partition problem, which in turn is equivalent to the graph-coloring problem. Computational experiments show that the heuristic procedure is effective in finding high-quality solutions to both the clique partition problem and the original grouping problem that includes additional costs.
DOI: 10.21233/p06g-hq44
title: Kehoe Lake ostracode surface sample dataset

description: Raw data for the Kehoe Lake ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/pgek-0z49
title: Wawig Lake ostracode surface sample dataset

description: Raw data for the Wawig Lake ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.6084/m9.figshare.28601087
title: Supplementary Material 9

description: CD-HIT (Cluster Database at High Identity with Tolerance) is a widely used clustering algorithm that reduces redundancy in large genomic datasets. CD-HIT can group similar sequences or genomic features when applied to machine learning results in Escherichia coli genomic analysis, improving model efficiency and reducing computational complexity.<b>CD-HIT in machine learning-based </b><b><i>E. coli</i></b><b> genomic analysis:</b><b>Feature reduction:</b> In supervised machine learning, CD-HIT can cluster similar sequences from genomic data, eliminating redundant information and improving feature selection for classifiers like Random Forest, XGBoost, and SVM.<b>Antimicrobial resistance (AMR) analysis:</b> By clustering resistance gene sequences at high identity thresholds (e.g., 90% or 95%), CD-HIT helps identify unique resistance patterns while reducing data redundancy.<b>Virulence gene clustering:</b> CD-HIT can be applied to virulence factor datasets to cluster homologous genes, aiding in classifying pathogenic <i>E. coli</i> strains.<b>Improving model generalization:</b> Reducing sequence redundancy prevents overfitting in machine learning models, leading to better generalization in predicting resistant and susceptible <i>E. coli</i> strains.<b>Computational efficiency:</b> CD-HIT optimizes data processing by clustering sequences before applying machine learning models, making large-scale genomic analyses more feasible.<b>CD-HIT results interpretation:</b><b>High identity clustering (e.g., 95-100%)</b>: Groups highly similar sequences, ensuring that only distinct genetic variations contribute to machine learning predictions.<b>Lower identity clustering (e.g., 70-90%)</b> Groups more diverse sequences, which is helpful for broader strain classification or identifying distant homologs in resistance genes.CD-HIT results help refine machine learning predictions in <i>E. coli</i> genomic analysis by ensuring that training data remains diverse and balanced.
DOI: 10.21233/8pa1-gf02
title: Seamons Mound [42UT271] vertebrate fauna dataset

description: Raw data for the Seamons Mound [42UT271] vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.6084/m9.figshare.28601144
title: Supplementary Material 10

description: Grouping antimicrobial resistance (AMR) genes based on their association with 16 antimicrobial classes used in antimicrobial susceptibility testing (AST) and <i>E. coli</i> treatment in ICU sepsis patients is crucial for understanding resistance patterns, guiding treatment decisions, and tracking the evolution of resistant strains.<b>Enhanced treatment strategies: </b>By categorizing AMR genes based on antimicrobial classes, clinicians can predict resistance trends in ICU <i>E. coli</i> sepsis cases, aiding in selecting effective antibiotics and reducing treatment failures.<b>Understanding phylogenetic distribution:</b> Phylogenetic grouping helps reveal whether specific resistance genes are associated with particular <i>E. coli</i> lineages, providing insights into the evolutionary dynamics and horizontal gene transfer events contributing to multidrug resistance.<b>Surveillance and outbreak tracking: </b>Clustering AMR genes by antimicrobial classes allows researchers to monitor the spread of resistant <i>E. coli</i> strains in ICU settings, identifying high-risk clones and resistance hotspots.<b>Correlation with phenotypic resistance:</b> Linking AMR gene clusters with AST results helps validate genotype-phenotype relationships, ensuring that genetic predictions align with observed drug resistance patterns.<b>Personalized medicine approaches: </b>Understanding the phylogenetic distribution of AMR genes supports the development of targeted therapies, potentially enabling the use of combination treatments to overcome specific resistance mechanisms.<b>AMR mechanism identification: </b>Categorizing resistance genes among antimicrobial classes provides deeper insights into resistance mechanisms, such as enzymatic degradation (e.g., β-lactamases for β-lactams), efflux pump activity, or target site modifications.<b>Antibiotic stewardship programs: </b>The data generated from such phylogenetic groupings can inform antimicrobial stewardship efforts by highlighting the most concerning resistance patterns and promoting the judicious use of antibiotics in ICU settings.By analyzing AMR gene distributions across antimicrobial classes and integrating phylogenetic data, researchers can develop robust strategies for combating drug-resistant <i>E. coli</i> infections in ICU patients with sepsis, ultimately improving clinical outcomes and slowing the spread of antimicrobial resistance.
DOI: 10.21233/9cgm-je58
title: Mukhrino Mire Complex testate amoebae surface sample dataset

description: Raw data for the Mukhrino Mire Complex testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.25421/yorksj.29037116
title: LM case control ITBS data.xlsx

description: This file contains the full data set for the case control study 'A sex-specific case-control analysis of iliotibial band syndrome in recreational runners comparing muscle function, gait analysis, training behaviours, psychological factors and sleep quality'. It includes each participants complete individual data, including demographics.
DOI: 10.11588/portal.gsi.6821ac8c41a9a
title: Kunsthandlung Marie Fritze
DOI: 10.11588/portal.gsi.6821ac8dbe0c9
title: Gemäldesalon Hugo Arnot
DOI: 10.11588/portal.gsi.6821ac8ec15ff
title: Galerie Banger (Zweigstelle Bad Nauheim)
DOI: 10.11588/portal.gsi.6821ac9024f76
title: Dr. Otto Burchard & Co. GmbH
DOI: 10.21233/9kgd-sg97
title: Gaodi testate amoebae surface sample dataset

description: Raw data for the Gaodi testate amoebae surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.6084/m9.figshare.28601384
title: Supplementary Material 11

description: Description of ANIclustermap's automated workflow.Calculate ANI between all-vs-all microbial genomes by fastANI (or skani).<br>If no similarity detected by fastANI, NA is output. In that case, NA is replaced by 0.0.<br>If previous result available at the time of re-run, reuse previous result.Clustering ANI matrix by scipy's UPGMA method.Using clustered matrix, draw ANI clustermap by seaborn.<pre><pre></pre></pre>
DOI: 10.21233/jxcr-tv75
title: Plußee pollen dataset

description: Raw data for the Plußee pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/tadv-5c57
title: Bass Pond pollen dataset

description: Raw data for the Bass Pond pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/63ta-3v77
title: Lake Maxin Kuckee water chemistry dataset

description: Raw data for the Lake Maxin Kuckee water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.11588/portal.gsi.6821acb304bfd
title: Buch- und Kunstantiquariat, Kunsthandlung Herbert Buber (Potsdam)
DOI: 10.11588/portal.gsi.6821acb41022f
title: Adolf Auer (Firma)
DOI: 10.11588/portal.gsi.6821acb524362
title: Bücherwurm, Buchhandlung, Antiquariat Gertrud Lübke
DOI: 10.11588/portal.gsi.6821acb6332d1
title: Fejér József Münzenhandlung (Budapest)
DOI: 10.11588/portal.gsi.6821acb7519c7
title: Otto Harrassowitz, Buchhandlung und Antiquariat
DOI: 10.15468/yq6jvt
title: Bee and hoverfly inventory in the western region of the Democratic Republic of Congo (Luki Biosphere Reserve)

description: At continental level, the lack of data on distribution and abundance characterizes wild pollinators in Africa, preventing any general assessment of their status. In the Democratic Republic of Congo, several regions have not yet been explored and pollinator data appear fragmentary, while some are still confined to grey literature. These data describe longitudinal sampling of bee and hoverfly communities in the Luki Biosphere Reserve in the DRC from 2021 to 2022 using three capture techniques (nets, coloured pantraps and horn traps).
DOI: 10.11588/portal.gsi.6821acb8828a5
title: Heinrich Hauser (München)
DOI: 10.11588/portal.gsi.6821acb9bbc3f
title: Heinrich Hugendubel (München)
DOI: 10.21233/tm91-9z37
title: E-isla pollen surface sample dataset

description: Raw data for the E-isla pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.11588/portal.gsi.6821acbadf924
title: Verlag Josef Kösel & Friedrich Pustet
DOI: 10.11588/portal.gsi.6821acbbc25a5
title: Alfred Lorentz (Leipzig)
DOI: 10.11588/portal.gsi.6821acbd4bca9
title: V. Zahn & Jaensch (Firma)
DOI: 10.11588/portal.gsi.6821acbe77681
title: Antiquariat Weiss (München)
DOI: 10.11588/portal.gsi.6821acbfedafa
title: Julius Weise's Hofbuchhandlung. Abteilung Antiquariat
DOI: 10.11588/portal.gsi.6821acc1829f2
title: Rudolph Weigel (Firma)
DOI: 10.21233/qn6s-d219
title: Square Lake diatom bottom sample dataset

description: Raw data for the Square Lake diatom bottom sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.11588/portal.gsi.6821acc2c61ad
title: Utopia Buchhandlung und Antiquariat (Berlin)
DOI: 10.11588/portal.gsi.6821acc42cc90
title: Tondeur & Säuberlich (Leipzig)
DOI: 10.11588/portal.gsi.6821acc596a6e
title: Taussig & Taussig (Prag)
DOI: 10.11588/portal.gsi.6821acc6aacca
title: Süddeutsches Antiquariat (München)
DOI: 10.11588/portal.gsi.6821acc7c64d8
title: Hugo Streisand Buchhandlung und Antiquariat (Berlin)
DOI: 10.15468/dl.b3pcmf
title: Occurrence Download

description: A dataset containing 331 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyloxalus sauli (Edwards, 1974)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 331 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025906-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11588/portal.gsi.6821acc8d47b1
title: Ferdinand Steinkopf (Stuttgart)
DOI: 10.11588/portal.gsi.6821acc9f32d9
title: August Späth, Buchhandlung und Antiquariat
DOI: 10.11588/portal.gsi.6821accb1a64e
title: Seuffer und Willi
DOI: 10.21233/e16w-yb23
title: Paupack diatom surface sample dataset

description: Raw data for the Paupack diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.11588/portal.gsi.6821accc68cf6
title: Eugen Seligmann, Münzenhandlung
DOI: 10.15468/dl.tnq6xa
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((15.67 47.35,15.72 47.35,15.72 47.4,15.67 47.4,15.67 47.35))",
 "HasCoordinate is true",
 "IucnRedListCategory is one of (EX, EW, CR, EN, VU, NT)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025905-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21233/4pzc-sh12
title: LDDsite4804 ostracode surface sample dataset

description: Raw data for the LDDsite4804 ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/z72c-2070
title: LDDsite6515 water chemistry dataset

description: Raw data for the LDDsite6515 water chemistry dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/5mf8-f073
title: Stoyoma Tarn pollen surface sample dataset

description: Raw data for the Stoyoma Tarn pollen surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.21233/z1q2-xz53
title: Seeley Sand and Gravel (Stauffer Elephants 97 & 98] vertebrate fauna dataset

description: Raw data for the Seeley Sand and Gravel (Stauffer Elephants 97 & 98] vertebrate fauna dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.11588/portal.gsi.6821acf99f17d
title: Westfälisches Antiquariat Ignaz Seiling
DOI: 10.15454/x23kjf/3dwtyw
title: ITS2-9P_S75_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/4llxxc
title: ITS1-10D_S44_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/50ndex
title: NCextP-ITS1_S65_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/8iocn6
title: ITS2-15D_S97_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/9u5nts
title: NC-ITS1_S66_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/bkktle
title: ITS1-6P_S24_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/bpgown
title: ITS1-9Pprime_S43_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/bwh215
title: Lib22_GAACCGCG-TAAGGTCA-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/bxmtr1
title: ITS2-16Pprime_S98_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/evf4up
title: ITS2-3P_S69_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/fl7ovw
title: ITS2-11P_S77_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/gnimzm
title: ITS2-1P_S67_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/grgwav
title: Lib17_AACTGTAG-TGCGGCGT-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/guwzyy
title: ITS2-10P_S76_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/i6rbeg
title: ITS2-7P_S73_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/iitkth
title: ITS1-12P_S30_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/jlmios
title: Lib3_TTCCTGTT-AAGATACT-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/jnkmpm
title: Lib10_TGGCCGGT-GCGCTCTA-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/k5b3oj
title: ITS1-VOP-rep_S63_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/kz7nz9
title: ITS2-VOP-rep_S107_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/l9hpbf
title: Lib21_AGGTTATA-CGGAACTG-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/lnj7fm
title: ITS1-3D_S37_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/mevrtr
title: ITS1-6P_S24_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/mj0dce
title: Lib26_CGCTATGT-GTGTCGGA-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/mj2dng
title: Lib1_ACACTAAG-ATATGGAT-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/mksrsg
title: Lib16_GTGAATAT-GAATGAGA-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/ni1vzf
title: ITS1-4P_S22_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/njed3f
title: Lib27_GTATGTTC-TTCCTGTT-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/nsa1fn
title: ITS1-11D_S45_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/ob4w8u
title: ITS1-5D_S39_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/p5c41e
title: Lib29_TACTCATA-GCCACAGG-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/pc8hce
title: ITS2-4P_S70_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/pcojii
title: Lib7_ACTCGTGT-GTTCCAAT-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/prvoov
title: Lib5_GCCACAGG-ATGGCATG-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/pvchq9
title: ITS1-12P_S30_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/q56kok
title: Lib9_CAATTAAC-ATATCTCG-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/qqlj0r
title: ITS1-7D_S41_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/rllaww
title: ITS1-CTP_S53_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/rpbi2f
title: ITS2-5P_S71_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/rrltne
title: Lib14_CATAGAGT-TGGTGGCA-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/sbx9ow
title: ITS2-2P_S68_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/tuyp8p
title: ITS1-INRAD_S58_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/wghfk4
title: ITS2-2P_S68_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/xjphio
title: ITS1-15P_S33_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/xlmqxj
title: ITS1-3D_S37_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/xws486
title: ITS1-CTD_S57_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/y6xvke
title: ITS1-11D_S45_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/yg2qh9
title: ITS2-3P_S69_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/ymdehf
title: ITS1-8D_S42_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/z3vsmn
title: ITS1-2D_S36_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/z7vwom
title: Lib15_ACAGGCGC-AGGCAGAG-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/08zndt
title: ITS2-15P_S81_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/1whezq
title: ITS2-INRAP_S102_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/2grksm
title: ITS2-VOP_S99_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/2vklsj
title: ITS1-SPD_S56_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/3x41xb
title: Lib19_CTGCTTCC-GATCTATC-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/4ztpuw
title: ITS1-15D_S49_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/592vne
title: ITS1-INRAD-rep_S62_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/5xo5af
title: Lib9_CAATTAAC-ATATCTCG-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/6dnozp
title: ITS2-8D_S90_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/6e8mze
title: ITS1-10P_S28_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/7igkjt
title: ITS1-11P_S29_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/auwc0h
title: Lib26_CGCTATGT-GTGTCGGA-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/b1sexe
title: ITS1-15D_S49_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/bykysh
title: ITS1-1P_S19_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/cjdnnt
title: Lib12_GACGTCTT-GGTGAACC-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/cqmabr
title: ITS2-5D_S87_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/dwcdtq
title: ITS2-10P_S76_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/e41rj9
title: ITS2-6D_S88_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/exxaa0
title: ITS1-CTD-rep_S61_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/ffgun6
title: ITS2-CTP_S101_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/fkxfxl
title: NcextP-ITS2_S112_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/fybo90
title: ITS2-10D_S92_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/g2c9en
title: ITS1-5P_S23_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/gkese7
title: ITS1-SPP_S52_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/gl4kpj
title: ITS1-7D_S41_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/hticex
title: Lib6_ATTGTGAA-GCAATGCA-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/ihhqi4
title: ITS1-2D_S36_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/j4b8ep
title: ITS2-VOD_S103_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/jx7shq
title: ITS2-INRAP-ref_S110_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/lhdxnb
title: ITS2-5P_S71_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/m8oo6t
title: ITS1-12D_S46_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/mmfvuv
title: ITS2-15P_S81_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/ojfp0o
title: Lib8_GTCTACAC-ACCTTGGC-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/otx1ha
title: Lib28_ACGCACCT-CCTTCACC-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/pdnabm
title: ITS1-1D_S35_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/plzqbd
title: ITS1-VOD-rep_S59_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/qsj2bb
title: Lib13_TGCGAGAC-CAACAATG-AH2MC2BBXY_L007_R1.fastq.gz
DOI: 10.15454/x23kjf/s6q0f0
title: Lib13_TGCGAGAC-CAACAATG-AH2MC2BBXY_L007_R2.fastq.gz
DOI: 10.15454/x23kjf/skavyf
title: ITS1-12D_S46_L001_R1_001.fastq.gz
DOI: 10.15454/x23kjf/t976op
title: ITS1-14D_S48_L001_R2_001.fastq.gz
DOI: 10.15454/x23kjf/urpirp
title: Lib10_TGGCCGGT-GCGCTCTA-AH2MC2BBXY_L007_R1.fastq.gz