cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15131/shef.data.23556273.v1
title: Raw and processed data for "Bayesian Learning from Multi-Way EEG Feedback for Robot Navigation and Target Identification"

description: The contents of each file is described in README.txt and below:

 <em>easy.zip</em> - Raw EEG recordings.
 <em>concatNumStepsToCTI</em> - Concatenated data showing all numbers of steps to Correct Target Identifications.
 <em>multiwayMultifiltClassified_CV_p*.mat - </em>Classified movement action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.
 <em>GClassified_CV_p*.mat</em> - Classified target identification action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.
 <em>full_MTCI_MNS_tables.mat -</em>Tables containing average PTCI and MNS results for each participant at each stringency level of the Bayesian Inference strategy.
 <em>rand_react_B0pt1_B0pt9_tables.mat - </em>Tables containing average PTCI and MNS results for the random strategy, and each participant with the react strategy and Bayesian Inference at stringency of 0.1 and 0.9.
 <em>stepCountData.zip - </em>Zipped directory containing step counts for all runs of all participants on small and large grids using all strategies.

<br>
This work has been approved by the Automatic Control and Systems Engineering ethics committee, ethics reference number: 022698. This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral training partnership.
DOI: 10.26188/25222571
title: Research data for "Ab Initio-based Determination of Lanthanoid-Radical Exchange as Visualised by Inelastic Neutron Scattering"

description: Research data for "Ab Initio-based Determination of Lanthanoid-Radical Exchange as Visualised by Inelastic Neutron Scattering"
DOI: 10.26188/25222571.v1
title: Research data for "Ab Initio-based Determination of Lanthanoid-Radical Exchange as Visualised by Inelastic Neutron Scattering"

description: Research data for "Ab Initio-based Determination of Lanthanoid-Radical Exchange as Visualised by Inelastic Neutron Scattering"
DOI: 10.17632/jmz53xr4vt.1
title: Shape Memory Properties of Silica Nanoparticle Infused Photopolymer Composites

description: Shape Memory Properties of Silica Nanoparticle Infused Photopolymer Composites
DOI: 10.17632/jmz53xr4vt.2
title: Shape Memory Properties of Silica Nanoparticle Infused Photopolymer Composites 

description: Shape Memory Properties of Silica Nanoparticle Infused Photopolymer Composites
DOI: 10.17632/gcy3g4g42j.2
title: Cooperative pro-tumorigenic adaptation to oncogenic RAS through epithelial to mesenchymal plasticity

description: In breast cancers, aberrant activation of the RAS/MAPK pathway is strongly associated with mesenchymal features and stemness traits, suggesting an interplay between this mitogenic signaling pathway and epithelial-mesenchymal plasticity (EMP). By using inducible models of human mammary epithelial cells, we demonstrate herein that the oncogenic activation of RAS promotes ZEB1-dependent EMP, which is necessary for malignant transformation. Notably, EMP is triggered by the secretion of pro-inflammatory cytokines from neighboring RAS-activated senescent cells, with a prominent role for IL-6 and IL-1. 
Our data contrast with the common view of cellular senescence as a tumor suppressive mechanism and EMP as a process promoting late stages of tumor progression in response to signals from the tumor microenvironment. Indeed, we highlighted here a pro-tumorigenic cellular cooperation of RAS-activated mammary epithelial cells, which leverages on oncogene-induced senescence and EMP to trigger cellular reprogramming and tumor initiation.
DOI: 10.17632/j6y9zpppt4.1
title: Exploring Optimal Deep Tunnel Sewer Systems to Enhance Urban Pluvial Flood Resilience in the Gangnam Region, South Korea

description: Urban pluvial flooding is becoming a global concern, exacerbated by urbanization and climate change, especially in rapidly developing areas where existing sewer systems lag behind growth. In order to minimize a system's functional failures during extreme rainfalls, localized engineering solutions are required for urban areas chronically suffering from pluvial floods. This study critically evaluates the Deep Tunnel Sewer System (DTSS) as a robust gray infrastructure solution for enhancing urban flood resilience, with a case study in the Gangnam region of Seoul, South Korea. To do so, we integrated a one-dimensional sewer model with a rapid flood spreading model to identify optimal routes and conduit diameters for the DTSS, focusing on four flood-related metrics: the total flood volume, the flood duration, the peak flooding rate, and the number of flooded nodes. Our research also developed the Intensity-Duration-Frequency (IDF) surfaces in three dimensions, providing a correlation between simulated flood-related metrics and design rainfall characteristics to distinguish the effect of DTSS on flood risk reduction. Our findings demonstrate how highly engineered solutions can enhance urban flood resilience, but they may still face challenges during extreme events. This study contributes valuable insights to assist in rational decision-making and emergency management in the face of increasing urban pluvial flood risks.
DOI: 10.17632/57fvfvyttp.2
title: Stratification of atherosclerosis based on plasma metabolic states

description: Supplementary Material for the paper "Stratification of atherosclerosis based on plasma metabolic states".
DOI: 10.48524/swedpop-v3-0
title: Version 3 of harmonised data in SwedPop
DOI: 10.6084/m9.figshare.25123784
title: A dataset of soil potassium content and aggregate-associated potassium fraction in long-term biochar amended field

description: Our data was obtained from a field where biochar was applied for 9 years with different methods. The data contains three parts: 1) soil potassium content, including water-soluble potassium (WSK), exchangeable potassium (EK), non-exchangeable potassium (NEK), and total potassium (TK), 2) Soil Aggregate distribution and aggregate-associated EK, NEK, and TK pools; 3) Maize dry weight and potassium uptake. In the Excel file, different letters indicate significant differences among treatments at 0.05 level.
DOI: 10.6084/m9.figshare.25123784.v1
title: A dataset of soil potassium content and aggregate-associated potassium fraction in long-term biochar amended field

description: Our data was obtained from a field where biochar was applied for 9 years with different methods. The data contains three parts: 1) soil potassium content, including water-soluble potassium (WSK), exchangeable potassium (EK), non-exchangeable potassium (NEK), and total potassium (TK), 2) Soil Aggregate distribution and aggregate-associated EK, NEK, and TK pools; 3) Maize dry weight and potassium uptake. In the Excel file, different letters indicate significant differences among treatments at 0.05 level.
DOI: 10.25921/934x-bx02
title: ES80 Water Column Sonar Data Collected During IYSNWExplorer22
DOI: 10.5281/zenodo.10472795
title: Artificial real metagenomic reads

description: We created Nanopore and Illumina metagenomic datasets by combining real (non-simulated) sequencing reads into an artificial metagenomic dataset. By doing this, we can be highly confident of the true taxa for each read in the dataset.

We used samples which have matched Illumina and Nanopore sequencing to ensure that differences are purely driven by technological differences and not composition differences. For the human component we combined reads from three individuals in the 1000 Genomes Project with Nanopore data for the human component downloaded from the 1000G ONT Sequencing Consortium (https://millerlaboratory.com/1000G-ONT.html) and we provide URLs for each sample: HG00277 Finnish Male with Illumina NovaSeq 6000 (accession: ERR3241786) and Nanopore R10.4; NA19318 Luhya, Kenya Male with Illumina NovaSeq 6000 (accession: ERR3239713) and Nanopore R10.4 (basecalled with Dorado v0.3.4); HG03611 Bengali, Bangladesh Female with Illumina NovaSeq 6000 (accession: ERR3243073) and Nanopore R10.4 (basecalled with Dorado v0.3.4). Each human readset was randomly downsampled to 1Gbp using rasusa (v0.7.1). For the M. tuberculosis component we used Illumina HiSeq 4000 (accession: ERR245682) and Nanopore R10.3 (accession: ERR8170871) (note: we used R10.3 as there are no R10.4 M. tuberculosis WGS datasets publicly available). For the bacterial component, we used Illumina MiSeq (accession: ERR7255689) and Nanopore R10.4 (accession: ERR7287988) reads from the ZymoBIOMICS HMW DNA Standard D6322 (Zymo Research), which contains seven bacterial and one fungal strain(s) - none of which are Mycobacterium. We removed Nanopore reads from all datasets with a length less than 500bp and the M. tuberculosis and Zymo datasets were downsampled to 3Gbp with rasusa. All human, M. tuberculosis, and Zymo reads were combined into a single artificial metagenomic file.
DOI: 10.5281/zenodo.10472796
title: Artificial real metagenomic reads

description: We created Nanopore and Illumina metagenomic datasets by combining real (non-simulated) sequencing reads into an artificial metagenomic dataset. By doing this, we can be highly confident of the true taxa for each read in the dataset.

We used samples which have matched Illumina and Nanopore sequencing to ensure that differences are purely driven by technological differences and not composition differences. For the human component we combined reads from three individuals in the 1000 Genomes Project with Nanopore data for the human component downloaded from the 1000G ONT Sequencing Consortium (https://millerlaboratory.com/1000G-ONT.html) and we provide URLs for each sample: HG00277 Finnish Male with Illumina NovaSeq 6000 (accession: ERR3241786) and Nanopore R10.4; NA19318 Luhya, Kenya Male with Illumina NovaSeq 6000 (accession: ERR3239713) and Nanopore R10.4 (basecalled with Dorado v0.3.4); HG03611 Bengali, Bangladesh Female with Illumina NovaSeq 6000 (accession: ERR3243073) and Nanopore R10.4 (basecalled with Dorado v0.3.4). Each human readset was randomly downsampled to 1Gbp using rasusa (v0.7.1). For the M. tuberculosis component we used Illumina HiSeq 4000 (accession: ERR245682) and Nanopore R10.3 (accession: ERR8170871) (note: we used R10.3 as there are no R10.4 M. tuberculosis WGS datasets publicly available). For the bacterial component, we used Illumina MiSeq (accession: ERR7255689) and Nanopore R10.4 (accession: ERR7287988) reads from the ZymoBIOMICS HMW DNA Standard D6322 (Zymo Research), which contains seven bacterial and one fungal strain(s) - none of which are Mycobacterium. We removed Nanopore reads from all datasets with a length less than 500bp and the M. tuberculosis and Zymo datasets were downsampled to 3Gbp with rasusa. All human, M. tuberculosis, and Zymo reads were combined into a single artificial metagenomic file.
DOI: 10.5281/zenodo.8339940
title: Mycobacterium genus database

description: The database is built as a Mycobacterium-specific one. For this database, we used genome_updater.sh (v0.6.3; https://github.com/pirovc/genome_updater)


genome_updater.sh -d "refseq" -g "bacteria" -T "g__Mycobacterium" -f "genomic.fna.gz" -M "gtdb" -A 1 -m


In addition, we added 17 high-quality M. tuberculosis genomes to this collection (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).


The mtb.ids file lists the sequence identifiers for those sequences in the database which are M. tuberculosis.
DOI: 10.5281/zenodo.8339941
title: Mycobacterium genus database

description: The database is built as a <em>Mycobacterium</em>-specific one. For this database, we used genome_updater.sh (v0.6.3; https://github.com/pirovc/genome_updater) <pre><code>genome_updater.sh -d "refseq" -g "bacteria" -T "g__Mycobacterium" -f "genomic.fna.gz" -M "gtdb" -A 1 -m</code></pre> In addition, we added 17 high-quality <em>M. tuberculosis</em> genomes to this collection (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).
DOI: 10.5281/zenodo.8343322
title: Mycobacterium genus database

description: The database is built as a Mycobacterium-specific one. For this database, we used genome_updater.sh (v0.6.3; https://github.com/pirovc/genome_updater)


genome_updater.sh -d "refseq" -g "bacteria" -T "g__Mycobacterium" -f "genomic.fna.gz" -M "gtdb" -A 1 -m


In addition, we added 17 high-quality M. tuberculosis genomes to this collection (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).


The mtb.ids file lists the sequence identifiers for those sequences in the database which are M. tuberculosis.
DOI: 10.34740/kaggle/dsv/7627247
title: BBC News
DOI: 10.5281/zenodo.8339947
title: Mycobacterium tuberculosis database

description: This database contains the M. tuberculosis H37Rv reference genome (RefSeq accession GCF_000195955.2), plus 17 high-quality M. tuberculosis references from lineages 1-6 (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).
DOI: 10.5281/zenodo.8339948
title: Mycobacterium tuberculosis database

description: This database contains the M. tuberculosis H37Rv reference genome (RefSeq accession GCF_000195955.2), plus 17 high-quality M. tuberculosis references from lineages 1-6 (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).
DOI: 10.5281/zenodo.10660116
title: Chemical compositions of minerals from the alunite-jarosite group compiled from the published literature

description: This spreadsheet contains a compilation of chemical compositions for minerals in the alunite-jarosite group from published literature sources.  The database is intended to be representative rather than exhaustive, and may have overlooked some published data.
DOI: 10.5281/zenodo.10660117
title: Chemical compositions of minerals from the alunite-jarosite group compiled from the published literature

description: This spreadsheet contains a compilation of chemical compositions for minerals in the alunite-jarosite group from published literature sources.  The database is intended to be representative rather than exhaustive, and may have overlooked some published data.
DOI: 10.5281/zenodo.8339821
title: Mycobacterium representative kraken2 database

description: A kraken2 database built from the a representative Mycobacterium set of genomes. This archive contains the three files required by kraken2, hash.k2d, opts.k2d, and taxo.k2d, along with inspect.txt, which is obtained by running kraken2-inspect on the database.


The genomes for this database were downloaded wiuth genome_updater.sh (v0.6.3; https://github.com/pirovc/genome_updater) with one RefSeq genome from each species in the Mycobacteriaceae family, plus one RefSeq genome from each species in the following genera: Klebsiella, Escherichia, Salmonella, Enterobacter, Streptococcus, Staphylococcus, Pseudomonas, Xanthomonas, and Bifidobacterium.


genome_updater.sh -A "species:1" -m -a -M "gtdb" -f "genomic.fna.gz" -g "bacteria" -d "refseq" -T "f__Mycobacteriaceae,g__Klebsiella,g__Escherichia,g__Enterobacter,g__Salmonella,g__Streptococcus,g__Staphylococcus,g__Pseudomonas,g__Xanthomonas,g__Bifidobacterium" -o GTDB_Mycobacterium/ 


The python script prepare_kraken_fasta.py was then used to prepare the assemblies for use in kraken with the following command


python prepare_kraken_fasta.py -r -x GCF_932530395.1,GCF_017190695.1,GCF_020735285.1,GCA_014701265.1,GCF_000013925.1,GCF_016756075.1,GCF_010727125.1,GCF_001307545.1 -o Mycobacterium.fna -s assembly_summary.txt GTDB_Mycobacterium/


The database was then built with kraken2 using the following commands


kraken2-build --download-taxonomy --db db/
kraken2-build --add-to-library Mycobacterium.fna --db db/
kraken2-build --build --db db/ --threads 16
DOI: 10.5281/zenodo.8339822
title: Mycobacterium representative kraken2 database

description: A kraken2 database built from the a representative Mycobacterium set of genomes. This archive contains the three files required by kraken2, hash.k2d, opts.k2d, and taxo.k2d, along with inspect.txt, which is obtained by running kraken2-inspect on the database.


The genomes for this database were downloaded wiuth genome_updater.sh (v0.6.3; https://github.com/pirovc/genome_updater) with one RefSeq genome from each species in the Mycobacteriaceae family, plus one RefSeq genome from each species in the following genera: Klebsiella, Escherichia, Salmonella, Enterobacter, Streptococcus, Staphylococcus, Pseudomonas, Xanthomonas, and Bifidobacterium.


genome_updater.sh -A "species:1" -m -a -M "gtdb" -f "genomic.fna.gz" -g "bacteria" -d "refseq" -T "f__Mycobacteriaceae,g__Klebsiella,g__Escherichia,g__Enterobacter,g__Salmonella,g__Streptococcus,g__Staphylococcus,g__Pseudomonas,g__Xanthomonas,g__Bifidobacterium" -o GTDB_Mycobacterium/ 


The python script prepare_kraken_fasta.py was then used to prepare the assemblies for use in kraken with the following command


python prepare_kraken_fasta.py -r -x GCF_932530395.1,GCF_017190695.1,GCF_020735285.1,GCA_014701265.1,GCF_000013925.1,GCF_016756075.1,GCF_010727125.1,GCF_001307545.1 -o Mycobacterium.fna -s assembly_summary.txt GTDB_Mycobacterium/


The database was then built with kraken2 using the following commands


kraken2-build --download-taxonomy --db db/
kraken2-build --add-to-library Mycobacterium.fna --db db/
kraken2-build --build --db db/ --threads 16
DOI: 10.5281/zenodo.8339699
title: Kraken2 Human database

description: A kraken2 database built from just the Human library on 29/06/2023. This archive contains just the three files required by kraken2, hash.k2d, opts.k2d, and taxo.k2d.


The commands used to download and build this database are:


k2 download-taxonomy --db db/

k2 download-library --db db/ --library human

k2 build --kmer-len 35 --minimizer-len 31  --minimizer-spaces 7 --threads 8 --db db/
DOI: 10.5281/zenodo.8339700
title: Kraken2 Human database

description: A kraken2 database built from just the Human library on 29/06/2023. This archive contains just the three files required by kraken2, hash.k2d, opts.k2d, and taxo.k2d.


The commands used to download and build this database are:


k2 download-taxonomy --db db/

k2 download-library --db db/ --library human

k2 build --kmer-len 35 --minimizer-len 31  --minimizer-spaces 7 --threads 8 --db db/
DOI: 10.5281/zenodo.8339802
title: Clockwork database

description: This database (clockwork) contains common sputum contaminants along with a selection of NTM genomes and H37Rv - as used in the Clockwork pipeline (https://github.com/iqbal-lab-org/clockwork). In addition, we added 17 high-quality M. tuberculosis genomes to this collection (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).


The database was downloaded using the download_tb_reference_files.pl  script. The 17 MTB genomes were downloaded from https://doi.org/10.5281/zenodo.4147301.


The db.tsv file contains a mapping from the sequence identifier to the category of that assembly - i.e. human, TB, Bacteria etc.


The minimap2.db.acc2tax.tsv maps those sequences with known accession numbers to their taxonomic identifier.
DOI: 10.5281/zenodo.8339803
title: Clockwork database

description: This database (clockwork) contains common sputum contaminants along with a selection of NTM genomes and H37Rv - as used in the Clockwork pipeline (https://github.com/iqbal-lab-org/clockwork). In addition, we added 17 high-quality M. tuberculosis genomes to this collection (from https://doi.org/10.1186/s13059-021-02474-0 - see mtb_gramtools_lineages.csv for the list of accessions).


The database was downloaded using the download_tb_reference_files.pl  script. The 17 MTB genomes were downloaded from https://doi.org/10.5281/zenodo.4147301.


The db.tsv file contains a mapping from the sequence identifier to the category of that assembly - i.e. human, TB, Bacteria etc.


The minimap2.db.acc2tax.tsv maps those sequences with known accession numbers to their taxonomic identifier.
DOI: 10.5281/zenodo.8339790
title: Simulated Illumina metagenomic reads

description: We simulated metagenomic Illumina sequencing reads to a mixture ratio that approximates that found in patient sputa, albeit with a slightly higher mycobacterial component. In total, 0.9 gigabases were generated, at proportions: 46% each for bacteria and human, 6\% Mycobacterium tuberculosis complex (MTBC), and 1% each for virus and non-tuberculous mycobacteria (NTM).


The reference genomes that reads were simulated from for these groups were gathered as follows. The references for the virus group were obtained using kraken's (v2.1.2) --download-library functionality. The viral library was downloaded on June 15 2023. The human genome from which the reads were simulated was KOREF_S1v2.1 (RefSeq accession GCA_020497085.1), with contigs shorter than 10kbp removed. The bacterial references were obtained by first downloading the bacteria library through kraken, followed by a subsampling due to the size (166Gb) of the resulting FASTA file. We subsampled the file by first removing sequences with a length <50kbp. We then extracted each sequence into its own FASTA file under a directory for the genus of the sequence - excluding the Mycobacterium genus. Genera were randomly subsampled to contain a maximum of 1000 assemblies. Each genus was then reduced to a representative subset using Assembly Dereplicator (commit 2dfcb14; https://github.com/rrwick/Assembly-Dereplicator) by keeping only 10% of the assemblies for each genus (-f 0.1). The NTM references selected were M. abscessus (accession GCF_017190695.1), M. avium (GCF_020735285.1), M. kansasii (GCA_014701265.1), M. ulcerans (GCF_000013925.1), M. intracellulare (GCF_016756075.1), M. terrae (GCF_010727125.1), and M. fortuitum (GCF_001307545.1). The MTBC reference is a lineage 1 assembly (GCF_932530395.1).


Illumina reads were simulated with ART (v2016.06.05). We simulated paired reads from a MiSeq v3 system (-ss MSv3) with a read length of 150, a mean fragment length of 250 and fragment length standard deviation 10 (-l 150 -m 250 -s 10).


We removed simulated Illumina reads with any ambiguous base.