cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3475205.v1
title: LUBM execution on 1 mix with 1 and 16 users on 20University dataset

description: Executing LUBM [1] Benchmark on 20 University dataset (generated with LUBM Data Generator [1] (dataset can be found here https://drive.google.com/open?id=0B3o07GMGMCvabl9ldkdhQWY4c3c) <br><br>- Executing against virtuoso7, fuseki 2.3.0 (Jena tdb), blazegraoh 1.5.3 on standard settings<br>- Dataset has 20 Universities<br>- The 14 Queries can be found here [2] (be aware that iguana need each query in one own line)<br>- Upload took:<br> - Blazegraph: 78580ms<br> - Virtuoso: 10633ms<br> - Fuseki: 31000ms<br><br>File Description:<br>- lubm_1-mix_1-user_qps.pdf : 1 Query Mix of 14 queries with 1 querying user (metrics: Queries Per Second)<br>- lubm_1-mix_16-user_qps.pdf : 1 Query Mix of 14 queries with 16 querying user (metrics: Queries Per Second) <br>- lubm_small.gnumeric : gnumeric file for the figures<br>- results_lubm_small.zip : Raw results<br><br>-------<br>[1] http://swat.cse.lehigh.edu/projects/lubm/<br>[2] http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt <br>
DOI: 10.6084/m9.figshare.3475205.v2
title: LUBM execution on 1 mix as well as 1hour with 1 and 16 users on 20University dataset

description: Executing LUBM [1] Benchmark on 20 University dataset (generated with LUBM Data Generator [1] (dataset can be found here https://drive.google.com/open?id=0B3o07GMGMCvabl9ldkdhQWY4c3c) <br><br>- Executing against virtuoso7, fuseki 2.3.0 (Jena tdb), blazegraoh 1.5.3 on standard settings<br>- Dataset has 20 Universities<br>- The 14 Queries can be found here [2] (be aware that iguana need each query in one own line)<br>- Upload took:<br> - Blazegraph: 78580ms<br> - Virtuoso: 10633ms<br> - Fuseki: 31000ms<br>- Querying 1 mix as well as 1 hour<br><br>File Description:<br>- lubm_1-mix_1-user_qps.pdf : 1 Query Mix of 14 queries with 1 querying user (metrics: Queries Per Second)<br>- lubm_1-mix_16-user_qps.pdf : 1 Query Mix of 14 queries with 16 querying user (metrics: Queries Per Second) <br>- lubm_small.gnumeric : gnumeric file for the figures<br>- results_lubm_small.zip : Raw results for mix benchmark<br><br>- lubm_1-hour_16-user_qps.pdf : 1 hour of 14 queries with 16 querying users (metrics Queries Per Second)<br>- lubm_1-hour_16-user_qmph.pdf : 1 hour of 14 queries with 16 querying users (metrics Query Mixes Per Hour)<br>- lubm_1-hour_16-user_no-of-queries.pdf : 1 hour of 14 queries with 16 querying users (metrics No of Queries per Hour)<br>- lubm_hour.gnumeric : gnumeric file for hour figures<br>- results_lubm_hour.zip : Raw results for hour benchmark<br><br>-------<br>[1] http://swat.cse.lehigh.edu/projects/lubm/<br>[2] http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt <br>
DOI: 10.6084/m9.figshare.3475205.v3
title: LUBM execution on 1 mix as well as 1hour with 1 and 16 users on 20University dataset

description: Executing LUBM [1] Benchmark on 20 University dataset (generated with LUBM Data Generator [1] (dataset can be found here https://drive.google.com/open?id=0B3o07GMGMCvabl9ldkdhQWY4c3c) <br><br>- Executing against virtuoso7, fuseki 2.3.0 (Jena tdb), blazegraoh 1.5.3 on standard settings<br>- Dataset has 20 Universities<br>- The 14 Queries can be found here [2] (be aware that iguana need each query in one own line)<br>- Upload took:<br> - Blazegraph: 78580ms<br> - Virtuoso: 10633ms<br> - Fuseki: 31000ms<br>- Querying 1 mix as well as 1 hour<br><br>File Description:<br>- lubm_1-mix_1-user_qps.pdf : 1 Query Mix of 14 queries with 1 querying user (metrics: Queries Per Second)<br>- lubm_1-mix_16-user_qps.pdf : 1 Query Mix of 14 queries with 16 querying user (metrics: Queries Per Second) <br>- lubm_small.gnumeric : gnumeric file for the figures<br>- results_lubm_small.zip : Raw results for mix benchmark<br><br>- lubm_1-hour_16-user_qps.pdf : 1 hour of 14 queries with 16 querying users (metrics Queries Per Second)<br>- lubm_1-hour_16-user_qmph.pdf : 1 hour of 14 queries with 16 querying users (metrics Query Mixes Per Hour)<br>- lubm_1-hour_16-user_no-of-queries.pdf : 1 hour of 14 queries with 16 querying users (metrics No of Queries per Hour)<br>- lubm_hour.gnumeric : gnumeric file for hour figures<br>- results_lubm_hour.zip : Raw results for hour benchmark<br><br>-------<br>[1] http://swat.cse.lehigh.edu/projects/lubm/<br>[2] http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt <br>
DOI: 10.6084/m9.figshare.3475205.v4
title: LUBM execution on 1 mix as well as 1hour with 1 and 16 users on 20University dataset

description: Executing LUBM [1] Benchmark on 20 University dataset (generated with LUBM Data Generator [1] (dataset can be found here https://drive.google.com/open?id=0B3o07GMGMCvabl9ldkdhQWY4c3c) <br><br>- Executing against virtuoso7, fuseki 2.3.0 (Jena tdb), blazegraoh 1.5.3 on standard settings<br>- Dataset has 20 Universities<br>- The 14 Queries can be found here [2] (be aware that iguana need each query in one own line)<br>- Upload took:<br> - Blazegraph: 78580ms<br> - Virtuoso: 10633ms<br> - Fuseki: 31000ms<br>- Querying 1 mix as well as 1 hour<br><br>File Description:<br>- lubm_1-mix_1-user_qps.pdf : 1 Query Mix of 14 queries with 1 querying user (metrics: Queries Per Second)<br>- lubm_1-mix_16-user_qps.pdf : 1 Query Mix of 14 queries with 16 querying user (metrics: Queries Per Second) <br>- lubm_small.gnumeric : gnumeric file for the figures<br>- results_lubm_small.zip : Raw results for mix benchmark<br><br>- lubm_1-hour_16-user_qps.pdf : 1 hour of 14 queries with 16 querying users (metrics Queries Per Second)<br>- lubm_1-hour_16-user_qmph.pdf : 1 hour of 14 queries with 16 querying users (metrics Query Mixes Per Hour)<br>- lubm_1-hour_16-user_no-of-queries.pdf : 1 hour of 14 queries with 16 querying users (metrics No of Queries per Hour)<br>- lubm_hour.gnumeric : gnumeric file for hour figures<br>- results_lubm_hour.zip : Raw results for hour benchmark<br><br>-------<br>[1] http://swat.cse.lehigh.edu/projects/lubm/<br>[2] http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt <br>
DOI: 10.6084/m9.figshare.3475205.v6
title: LUBM execution on 1 mix as well as 1hour with 1 and 16 users on 20University dataset

description: Executing LUBM [1] Benchmark on 20 University dataset (generated with LUBM Data Generator [1]) <br><br>- Executing against virtuoso7, fuseki 2.3.0 (Jena tdb), blazegraoh 1.5.3 on standard settings<br>- Dataset has 20 Universities<br>- The 14 Queries can be found here [2] (be aware that iguana need each query in one own line)<br>- Upload took:<br> - Blazegraph: 78580ms<br> - Virtuoso: 10633ms<br> - Fuseki: 31000ms<br>- Querying 1 mix as well as 1 hour<br><br>File Description:<br>- lubm_1-mix_1-user_qps.pdf : 1 Query Mix of 14 queries with 1 querying user (metrics: Queries Per Second)<br>- lubm_1-mix_16-user_qps.pdf : 1 Query Mix of 14 queries with 16 querying user (metrics: Queries Per Second) <br>- lubm_small.gnumeric : gnumeric file for the figures<br>- results_lubm_small.zip : Raw results for mix benchmark<br><br>- lubm_1-hour_16-user_qps.pdf : 1 hour of 14 queries with 16 querying users (metrics Queries Per Second)<br>- lubm_1-hour_16-user_qmph.pdf : 1 hour of 14 queries with 16 querying users (metrics Query Mixes Per Hour)<br>- lubm_1-hour_16-user_no-of-queries.pdf : 1 hour of 14 queries with 16 querying users (metrics No of Queries per Hour)<br>- lubm_hour.gnumeric : gnumeric file for hour figures<br>- results_lubm_hour.zip : Raw results for hour benchmark<br><br>-------<br>[1] http://swat.cse.lehigh.edu/projects/lubm/<br>[2] http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt <br>
DOI: 10.6084/m9.figshare.3475205.v5
title: LUBM execution on 1 mix as well as 1hour with 1 and 16 users on 20University dataset

description: Executing LUBM [1] Benchmark on 20 University dataset (generated with LUBM Data Generator [1]) <br><br>- Executing against virtuoso7, fuseki 2.3.0 (Jena tdb), blazegraoh 1.5.3 on standard settings<br>- Dataset has 20 Universities<br>- The 14 Queries can be found here [2] (be aware that iguana need each query in one own line)<br>- Upload took:<br> - Blazegraph: 78580ms<br> - Virtuoso: 10633ms<br> - Fuseki: 31000ms<br>- Querying 1 mix as well as 1 hour<br><br>File Description:<br>- lubm_1-mix_1-user_qps.pdf : 1 Query Mix of 14 queries with 1 querying user (metrics: Queries Per Second)<br>- lubm_1-mix_16-user_qps.pdf : 1 Query Mix of 14 queries with 16 querying user (metrics: Queries Per Second) <br>- lubm_small.gnumeric : gnumeric file for the figures<br>- results_lubm_small.zip : Raw results for mix benchmark<br><br>- lubm_1-hour_16-user_qps.pdf : 1 hour of 14 queries with 16 querying users (metrics Queries Per Second)<br>- lubm_1-hour_16-user_qmph.pdf : 1 hour of 14 queries with 16 querying users (metrics Query Mixes Per Hour)<br>- lubm_1-hour_16-user_no-of-queries.pdf : 1 hour of 14 queries with 16 querying users (metrics No of Queries per Hour)<br>- lubm_hour.gnumeric : gnumeric file for hour figures<br>- results_lubm_hour.zip : Raw results for hour benchmark<br><br>-------<br>[1] http://swat.cse.lehigh.edu/projects/lubm/<br>[2] http://swat.cse.lehigh.edu/projects/lubm/queries-sparql.txt <br>
DOI: 10.6084/m9.figshare.3475058
title: Raw Data for FEA models of the labeled Shells

description: Raw data for PeerJ manuscript: Comparative cephalopod shell strength and the role of septum morphology on stress distribution.<br>Files include nodal values for displacement magnitude and principal stresses for all models used in the above study.<br><br><br><br><br><br><br><br><br>
DOI: 10.6084/m9.figshare.3475034.v4
title: Series Representation of Power Function

description: <b>Abstract</b>. This paper presents the way to make expansion for the next form function: $y =x^n , ∀(x,n) ∈ N$ to the numerical series. The most widely used methods to solve this problem are Newton’s Binomial Theorem and Fundamental Theorem of Calculus (that is, derivative and integral are inverse operators). The paper provides the other kind of solution, except above described theorems.<br><br> <b>arXiv</b>:1603.02468 <b><br>MSC 2010</b>:<b> </b>40C15, 32A05<br> <b>DOI</b>: 10.6084/m9.figshare.3475034 <br><b>Keywords:</b> power, power function, monomial, polynomial, power series, third power, series, finite difference, divided difference, high order finite difference, derivative, binomial coefficient, binomial theorem, Newton's binomial theorem, binomial expansion, n-th difference of n-th power, number theory, cubic number, cube, Euler number, exponential function, Pascal triangle, Pascal’s triangle, mathematics, math, maths, arxiv, science, preprint, математика, наука, algebra, analysis, calculus, open science<br>
DOI: 10.6084/m9.figshare.3475007
title: Supplementary Data - Lopez-Escardo et al. 2018

description: Supplementary data for the Manuscript Lopez-Escardo et al. 2018 entitled "<i>Metabarcoding analysis on European coastal samples reveals new marine metazoan diversity". </i>Containing the 18S rRNA Metazoan reference database, alignments and phylogenetic trees, and the OTU table.
DOI: 10.6084/m9.figshare.3475007.v1
title: Supplementary Data Lopez-Escardo et al. 2016

description: Supplementary data for the Manuscript submitted to Molecular Ecology; Lopez-Escardo et al. 2016 "<i>Metabarcoding analysis reveals new marine metazoan diversity" </i>including 18S rRNA Metazoan reference database and OTU table.
DOI: 10.6084/m9.figshare.3474950
title: DBPSBv2 execution on 16 querying user

description: Collection of raw results, figures and gnumeric file for the figures of the execution of the DBPSBv2 queries with IGUANA on an 400M Triple Dbpedia dataset.<br><br>- results_again.zip : raw results<br>- results_dbpsb.gnumeric : gnumeric file to create the figures<br>- dbpsb_16_qmph.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: Query Mixes Per Hour)<br>- dbpsb_16_no-of-queries.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: No of queries Per Hour)<br>- dbpsb_16-1_qps.pdf : Figure for 16 querying users and 1 update user (Metric: Query Per Second)<br>- dbpsb_16-0_qps.pdf : Figure for 16 querying users and no update user (Metric: Query Per Second)<br>
DOI: 10.6084/m9.figshare.3474950.v1
title: DBPSBv2 execution on 16 querying user

description: Collection of raw results, figures and gnumeric file for the figures of the execution of the DBPSBv2 queries with IGUANA on an 400M Triple Dbpedia dataset.<br><br>- results_again.zip : raw results<br>- results_dbpsb.gnumeric : gnumeric file to create the figures<br>- dbpsb_16_qmph.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: Query Mixes Per Hour)<br>- dbpsb_16_no-of-queries.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: No of queries Per Hour)<br>- dbpsb_16-1_qps.pdf : Figure for 16 querying users and 1 update user (Metric: Query Per Second)<br>- dbpsb_16-0_qps.pdf : Figure for 16 querying users and no update user (Metric: Query Per Second)<br>
DOI: 10.6084/m9.figshare.3474950.v2
title: DBPSBv2 execution on 16 querying user

description: Collection of raw results, figures and gnumeric file for the figures of the execution of the DBPSBv2 queries with IGUANA on an 400M Triple Dbpedia dataset.<br><br>- results_again.zip : raw results<br>- results_dbpsb.gnumeric : gnumeric file to create the figures<br>- dbpsb_16_qmph.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: Query Mixes Per Hour)<br>- dbpsb_16_no-of-queries.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: No of queries Per Hour)<br>- dbpsb_16-1_qps.pdf : Figure for 16 querying users and 1 update user (Metric: Query Per Second)<br>- dbpsb_16-0_qps.pdf : Figure for 16 querying users and no update user (Metric: Query Per Second)<br>
DOI: 10.6084/m9.figshare.3474950.v3
title: DBPSBv2 execution on 16 querying user

description: Collection of raw results, figures and gnumeric file for the figures of the execution of the DBPSBv2 queries with IGUANA on an 400M Triple Dbpedia dataset.<br><br>- results_again.zip : raw results<br>- results_dbpsb.gnumeric : gnumeric file to create the figures<br>- dbpsb_16_qmph.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: Query Mixes Per Hour)<br>- dbpsb_16_no-of-queries.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: No of queries Per Hour)<br>- dbpsb_16-1_qps.pdf : Figure for 16 querying users and 1 update user (Metric: Query Per Second)<br>- dbpsb_16-0_qps.pdf : Figure for 16 querying users and no update user (Metric: Query Per Second)<br>
DOI: 10.6084/m9.figshare.3474950.v4
title: DBPSBv2 execution on 16 querying user

description: Collection of raw results, figures and gnumeric file for the figures of the execution of the DBPSBv2 queries with IGUANA on an 400M Triple Dbpedia dataset.<br><br>- results_again.zip : raw results<br>- results_dbpsb.gnumeric : gnumeric file to create the figures<br>- dbpsb_16_qmph.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: Query Mixes Per Hour)<br>- dbpsb_16_no-of-queries.pdf : Figure for 16 querying users and a comparison between 0 and 1 update user (Metric: No of queries Per Hour)<br>- dbpsb_16-1_qps.pdf : Figure for 16 querying users and 1 update user (Metric: Query Per Second)<br>- dbpsb_16-0_qps.pdf : Figure for 16 querying users and no update user (Metric: Query Per Second)<br>
DOI: 10.6084/m9.figshare.3474752
title: data for Additiona file 14, 15 and 16. Multiple sequence alignment of LRR-RLK kinase domains.

description: Additional file 14. Multiple sequence alignment of LRR-RLK kinase domains from <i>Citrus clementina</i> and <i>Arabidopsis thaliana</i>. Protein sequences alignment was performed with MAFFT using the G-INS-i strategy. TrimAL v.1.3. was used to trim the alignment.Additional file 15. Multiple sequence alignment of LRR-RLK kinase domains from <i>Citrus sinensis</i> and <i>Arabidopsis thaliana</i>. Protein sequences alignment was performed with MAFFT using the G-INS-i strategy. TrimAL v.1.3. was used to trim the alignment.Additional file 16. Multiple sequence alignment of LRR-XII from <i>Citrus sinensis, Citrus clementina </i>and<i> Arabidopsis thaliana</i>. Protein sequences alignment was performed with MAFFT using the G-INS-i strategy. TrimAL v.1.3. was used to trim the alignment. <br>
DOI: 10.6084/m9.figshare.3474752.v1
title: data for Additiona file 14, 15 and 16. Multiple sequence alignment of LRR-RLK kinase domains.

description: Additional file 14. Multiple sequence alignment of LRR-RLK kinase domains from <i>Citrus clementina</i> and <i>Arabidopsis thaliana</i>. Protein sequences alignment was performed with MAFFT using the G-INS-i strategy. TrimAL v.1.3. was used to trim the alignment.Additional file 15. Multiple sequence alignment of LRR-RLK kinase domains from <i>Citrus sinensis</i> and <i>Arabidopsis thaliana</i>. Protein sequences alignment was performed with MAFFT using the G-INS-i strategy. TrimAL v.1.3. was used to trim the alignment.Additional file 16. Multiple sequence alignment of LRR-XII from <i>Citrus sinensis, Citrus clementina </i>and<i> Arabidopsis thaliana</i>. Protein sequences alignment was performed with MAFFT using the G-INS-i strategy. TrimAL v.1.3. was used to trim the alignment. <br>
DOI: 10.6084/m9.figshare.3474584
title: Pre- & Post-operative 3dMD Surface Scans

description: This folder contains the optical surface scans of the patients (with texture) in upright position, using the laser 3dMD system installed at the Royal Free Hospital.All image files can be opened up using the free-software Paraview (www.paraview.org).
DOI: 10.6084/m9.figshare.3474476
title: Paradiplozoon exposure

description: Raw data of exposure experimentation with <i>P. ichthyoxanthon</i> eggs and larvae. Calibration data and analysed Al levels in exposure media.<br>Authors may be contacted for access to raw data files.
DOI: 10.6084/m9.figshare.3474476.v1
title: Paradiplozoon exposure

description: Raw data of exposure experimentation with <i>P. ichthyoxanthon</i> eggs and larvae. Calibration data and analysed Al levels in exposure media.<br>Authors may be contacted for access to raw data files.
DOI: 10.6084/m9.figshare.3474464
title: Reconstruction of Ancestral beta-lactamase

description: Blast Result
DOI: 10.6084/m9.figshare.3474464.v1
title: Reconstruction of Ancestral beta-lactamase

description: Blast Result
DOI: 10.6084/m9.figshare.3474404.v1
title: CSV

description: Urai AE, Braun A and Donner TH. Decision uncertainty drives pupil-linked arousal systems and alters subsequent decision-making.
DOI: 10.6084/m9.figshare.3474293
title: Data From: A comparison of statistical emulation methodologies for multi-wave calibration of environmental models

description: Expensive computer codes, particularly those used simulating environmental or geological processes such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power. This was the case for the analysis that produced the UK climate projections in 2009. In this paper we compare the effectiveness of both emulation approaches upon a multi-wave calibration framework that is becoming popular in the climate modelling community called ``history matching". We find that Gaussian processes offer significant benefits to the reduction of parametric uncertainty over regression-only approaches. We find that in a multi-wave experiment, a combination of regression-only emulators initially, followed by Gaussian process emulators for refocussing experiments can be nearly as effective as using Gaussian processes throughout for a fraction of the computational cost. We also discover a number of design and emulator-dependent features of the multi-wave history matching approach that can cause apparent, yet premature, convergence of our estimates of parametric uncertainty. We compare these approaches to calibration in idealised examples and apply it to a well known geological reservoir model.
DOI: 10.6084/m9.figshare.3474293.v1
title: Data From: A comparison of statistical emulation methodologies for multi-wave calibration of environmental models

description: Expensive computer codes, particularly those used simulating environmental or geological processes such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power. This was the case for the analysis that produced the UK climate projections in 2009. In this paper we compare the effectiveness of both emulation approaches upon a multi-wave calibration framework that is becoming popular in the climate modelling community called ``history matching". We find that Gaussian processes offer significant benefits to the reduction of parametric uncertainty over regression-only approaches. We find that in a multi-wave experiment, a combination of regression-only emulators initially, followed by Gaussian process emulators for refocussing experiments can be nearly as effective as using Gaussian processes throughout for a fraction of the computational cost. We also discover a number of design and emulator-dependent features of the multi-wave history matching approach that can cause apparent, yet premature, convergence of our estimates of parametric uncertainty. We compare these approaches to calibration in idealised examples and apply it to a well known geological reservoir model.
DOI: 10.6084/m9.figshare.3474080
title: Crab and snail community responses to warming and ocean acidification

description: Lined shore crab feeding and growth data during acidification -temperature experiment
DOI: 10.6084/m9.figshare.3474080.v2
title: Crab and snail community responses to warming and ocean acidification

description: Lined shore crab feeding and growth data during acidification -temperature experiment
DOI: 10.6084/m9.figshare.3474080.v1
title: ICEMAN

description: Lined shore crab feeding and growth data during acidification -temperature experiment
DOI: 10.6084/m9.figshare.3474074
title: Marine archaea 5year surface to seafloor time-series representative sequences and legend

description: Fasta file contains representative 16S OTU sequences, chosen as the most abundant sequences in an OTU. The spreadsheet contains the OTU ID as given in the fasta file, the associated assigned taxonomy to the OTU and abbreviations used in analyses.<br>
DOI: 10.6084/m9.figshare.3474074.v1
title: Marine archaea 5year surface to seafloor time-series representative sequences and legend

description: Fasta file contains representative 16S OTU sequences, chosen as the most abundant sequences in an OTU. The spreadsheet contains the OTU ID as given in the fasta file, the associated assigned taxonomy to the OTU and abbreviations used in analyses.<br>
DOI: 10.6084/m9.figshare.3474065
title: Data used in PlosOne paper

description: Included all of data used in isolation paper submitted to PlosOne.
DOI: 10.6084/m9.figshare.3474065.v1
title: Data used in PlosOne paper

description: Included all of data used in isolation paper submitted to PlosOne.