cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5500677
title: SEED-G: Simulated EEG Data Generator for testing connectivity algorithms

description: SEED-G toolbox was developed in MATLAB environment (tested on version R2017a and R2020b) and released on the GitHub page https://github.com/aanzolin/SEED-G-toolbox (accessed date 12 April 2021). It is organized in the following subfolders: <strong>main</strong>: it is the core of the toolbox and contains all the functions for the generation of EEG data according to a predefined ground-truth network. <strong>dependencies</strong>: containing parts of other toolboxes required to successfully run SEED-G functions. The links to the full packages can be found in the documentation on the GitHub page. The additional packages are Brain Connectivity Toolbox (BCT) [40], FieldTrip [41], Multivariate Granger Causality Toolbox (MVGC) [24], and AsympPDC Package (PDC_AsympSt) [42,43]. Additionally, the implemented forward model is solved according to the New York Head (NYH) model, whose parameters are contained in the structure available on the ICBM-NY platform [28]. <strong>real data</strong>: containing real EEG data acquired from one healthy subject during resting state at scalp level (‘EEG_real_sources.mat’) and its reconstructed version in source domain (‘sLOR_cortical_sources.mat’). These signals can be employed to extract the AR components to be included in the model to generate data with the same spectral properties of the real ones. <strong>demo</strong>: containing examples of MATLAB scripts to be used to learn the different functionalities of the toolbox. For example, the code ‘run_generation.m’ allows to specify the directory containing the real sources and each specific input of the function ‘simulatedData_generation.m’. <strong>auxiliary functions</strong>: containing either original MATLAB functions or modified version of free available functions.
description: {"references": ["https://doi.org/10.3390/s21113632"]}
DOI: 10.5281/zenodo.5500729
title: Epizoanthus rinbou SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5500728
title: Epizoanthus rinbou SPAdes preassembly

description: .
DOI: 10.5066/p94q3kqm
title: Radiocarbon dating of an alluvial deposit with associated faunal remains

description: We assessed a construction site in the northern Las Vegas Valley that was initially reported as an "ice age" deposit. Alluvial deposits exposed at the site were inset into the Las Vegas Formation and contained semi-articulated Equus remains. Calibrated radiocarbon dates on two different materials associated with the remains centered on 1957, thus rendering the horse bones as modern.
DOI: 10.6084/m9.figshare.13636976
title: Grassland reclamation of a copper mine tailings facility: Long term effects of biosolids on plant community responses

description: <b>Aim</b>: We explore long-term plant community responses 17 years after a one-time application of biosolids (0, 50, 100, 150, 200, 250 dry Mg∙ha<sup>-1</sup>) to determine (1) whether the land application of biosolids on mine tailings, seeded with agronomic grass-legume mixture, affects long-term plant community responses, (2) how application rates and soil texture influenced plant community responses and community structure, and (3) whether native plant species have colonized and contributed to the reclaimed plant community. <b>Location</b>: Two tailings deposits (sand and silt loam) generated by a copper-molybdenum (Cu-Mo) mine in Southern British Columbia, Canada. <b>Methods:</b> Plant communities were sampled by visual evaluation of percent cover to the lowest taxonomical level possible. Vegetation surveys were completed on two mine tailings deposits within the storage facility that have different soil textures (sand and silt loam). <b>Results:</b> Results showed that the interaction of biosolids applications and soil texture impacted multiple community plant responses, including increasing plant cover at both sites, and increasing richness, evenness and diversity at the sandy site. Biosolids application enhanced the performance of spontaneously established species (volunteer species) and non-native/naturalized grasses. <b>Conclusion: </b>Our study demonstrated that biosolids application facilitates ecological succession by enhancing the establishment of non-native volunteer species over the long-term, which increases vegetative cover on both deposits and promotes plant communities diversity on sites with sandy soil texture. <br>
DOI: 10.6084/m9.figshare.13636976.v1
title: Grassland reclamation of a copper mine tailings facility: Long term effects of biosolids on plant community responses

description: <b>Aim</b>: We explore long-term plant community responses 17 years after a one-time application of biosolids (0, 50, 100, 150, 200, 250 dry Mg∙ha<sup>-1</sup>) to determine (1) whether the land application of biosolids on mine tailings, seeded with agronomic grass-legume mixture, affects long-term plant community responses, (2) how application rates and soil texture influenced plant community responses and community structure, and (3) whether native plant species have colonized and contributed to the reclaimed plant community. <b>Location</b>: Two tailings deposits (sand and silt loam) generated by a copper-molybdenum (Cu-Mo) mine in Southern British Columbia, Canada. <b>Methods:</b> Plant communities were sampled by visual evaluation of percent cover to the lowest taxonomical level possible. Vegetation surveys were completed on two mine tailings deposits within the storage facility that have different soil textures (sand and silt loam). <b>Results:</b> Results showed that the interaction of biosolids applications and soil texture impacted multiple community plant responses, including increasing plant cover at both sites, and increasing richness, evenness and diversity at the sandy site. Biosolids application enhanced the performance of spontaneously established species (volunteer species) and non-native/naturalized grasses. <b>Conclusion: </b>Our study demonstrated that biosolids application facilitates ecological succession by enhancing the establishment of non-native volunteer species over the long-term, which increases vegetative cover on both deposits and promotes plant communities diversity on sites with sandy soil texture. <br>
DOI: 10.17632/bdkbc7w8nk.1
title: Dataset - Hospitalisations and morbidities after paediatric traumatic brain injury in Germany

description: This data set was extracted from the DRG data set of the German Federal Bureau of Statistics. It contains aggregated data on diagnoses and procedures of all cases with primary or secondary diagnosis of traumatic brain injury between 2014 and 2018 that occurred in patients < 18 years. Person time was calculated from the German mid-year-populations of the corresponding years and is also included in the data set.
DOI: 10.17632/fkwyg6p8f7.1
title: Lower limb mechanical muscular power during vertical jumps by contact mat and Bosco’s equation

description: Lower limb MMP in a vertical jumping estimated by two on-field evaluation tools to sports performance, being a contact mat (MMPcontact_mat) and estimated by the Bosco’s equation (MMPBosco’s_equation).
DOI: 10.17632/jmc7hh53hh.2
title: Information and codes for construction of a  neural-fuzzy model-based recommendation system

description: This database contains all the codes and data used for the construction of a neural fuzzy recommendation system. Here, a detailed report and evaluation of this recommendation system are given in the article entitled "A two-stage location-sensitive and user preference-aware recommendation system".
DOI: 10.17632/cjxgx3m36h.1
title: Data for: Development of a process for obtaining non-mutagenic madder root (Rubia tinctorum) extract for textile dyeing

description: supplementary data to "Development of a process for obtaining non-mutagenic madder root (Rubia tinctorum) extract for textile dyeing"
DOI: 10.6084/m9.figshare.13172087
title: The Fitness Browser: Genome-wide mutant fitness data for diverse bacteria (November 2020 release)

description: This data set includes 6,570 genome-wide fitness experiments for 42 bacteria. Data were collected using pools of randomly barcoded transposons (RB-TnSeq). The sqlite3 database (feba.db) and BLAST database (aaseq) are included in the db.tar.gz. For the schema of the sqlite3 database, see feba/lib/db_setup_tables.sql in the source code (code.tar.gz). Or view the up-to-date code at https://bitbucket.org/berkeleylab/feba.<br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>
DOI: 10.6084/m9.figshare.13171766
title: RB-TnSeq data for Bacteroides thetaiotaomicron VPI-5482

description: This data set includes 523 successful fitness assays for Bacteroides thetaiotaomicron VPI-5482 based on a pool of randomly-barcoded transposon mutants (RB-TnSeq). The data is provided as a gzipped tarball. After unpacking, load index.html into a web browser to get some explanation of all the files.<br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>
DOI: 10.6084/m9.figshare.16606781
title: Supplementary 1.

description: <b>Complete genetic information of <i>Rickettsia</i> identified in <i>Ixodes dampfi </i>from Mexico. </b>
DOI: 10.6084/m9.figshare.16606781.v1
title: Supplementary 1.

description: <b>Complete genetic information of <i>Rickettsia</i> identified in <i>Ixodes dampfi </i>from Mexico. </b>
DOI: 10.6084/m9.figshare.7742855
title: Large-scale genetic characterization of the human gut commensal bacterium Bacteroides thetaiotaomicron

description: Genome-wide mutant fitness data for Bacteroides thetaiotaomicron VPI-5482 across 113 different conditions, including various carbon sources, nitrogen sources, and stresses.<br><br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>
DOI: 10.6084/m9.figshare.7742855.v1
title: Large-scale genetic characterization of the human gut commensal bacterium Bacteroides thetaiotaomicron

description: Genome-wide mutant fitness data for Bacteroides thetaiotaomicron VPI-5482 across 113 different conditions, including various carbon sources, nitrogen sources, and stresses.<br><br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>
DOI: 10.5281/zenodo.5500725
title: Dataset : Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps

description: <strong>The three files in the dataset are:</strong> 1) Healthy Sheep Atria Fibre Orientation Dataset 300µm 2) Heart Failure Sheep Atria Fibre Orientation Dataset 300µm 3) Human Atria Fibre Orientation Dataset 330µm <strong>Data is stored as numpy binary files. Given below is an example .py script to open the flat datasets:</strong> import numpy as np<br> data = np.load("Human_330um.npy") <strong>Volume and fibre orientation dataset stored in flat format as given below:</strong> i, j, k, v1, v2, v3, ... repeated for each voxel where (i, j, k) are voxel coordinates and (v1, v2, v3) are vector components corresponding to fibre orientation within that voxel.
description: The code used to generate the spatial networks is available at : github.com/JamesAlecColeman/reentrySpatialNetworks
DOI: 10.6084/m9.figshare.5134840
title: The Fitness Browser: Genome-wide mutant fitness data for diverse bacteria (June 2017 release)

description: As of June 2017, the Fitness Browser contains 4,956 genome-wide fitness assays from 33 bacteria. This download includes the data and code needed to run the fitness browser web site, including all of the per-gene and per-strain fitness values. See the README.txt file for more information about how to use these files, or visit the interactive Fitness Browser (http://fit.genomics.lbl.gov/).<br><br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>
DOI: 10.5281/zenodo.5500724
title: Dataset : Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps

description: <strong>The three files in the dataset are:</strong> 1) Healthy Sheep Atria Fibre Orientation Dataset 300µm 2) Heart Failure Sheep Atria Fibre Orientation Dataset 300µm 3) Human Atria Fibre Orientation Dataset 330µm <strong>Data is stored as numpy binary files. Given below is an example .py script to open the flat datasets:</strong> import numpy as np<br> data = np.load("Human_330um.npy") <strong>Volume and fibre orientation dataset stored in flat format as given below:</strong> i, j, k, v1, v2, v3, ... repeated for each voxel where (i, j, k) are voxel coordinates and (v1, v2, v3) are vector components corresponding to fibre orientation within that voxel.
description: The code used to generate the spatial networks is available at : github.com/JamesAlecColeman/reentrySpatialNetworks
DOI: 10.6084/m9.figshare.5134837
title: Data Downloads for "Deep Annotation of Protein Function across Diverse Bacteria from Mutant Phenotypes"

description: These downloads include genome-wide fitness data for 32 bacteria (seven more than in the bioRxiv preprint). The easiest way to view the data is with the Fitness Browser (http://fit.genomics.lbl.gov) rather than with these downloads. These downloads include: an R image with all of the per-gene fitness values and analyses; metadata about the 32 bacteria; a gzipped tar file of genome sequences, protein sequences, and gene models; and a gzipped tar file of strain usage. See the README.txt file for more explanation.<br><br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>
DOI: 10.6084/m9.figshare.5134837.v2
title: Data Downloads for "Deep Annotation of Protein Function across Diverse Bacteria from Mutant Phenotypes"

description: These downloads include genome-wide fitness data for 32 bacteria (seven more than in the bioRxiv preprint). The easiest way to view the data is with the Fitness Browser (http://fit.genomics.lbl.gov) rather than with these downloads. These downloads include: an R image with all of the per-gene fitness values and analyses; metadata about the 32 bacteria; a gzipped tar file of genome sequences, protein sequences, and gene models; and a gzipped tar file of strain usage. See the README.txt file for more explanation.<br><br>Note added September 10, 2021: After publishing this data, Morgan Price and Adam Deutschbauer discovered that our stock solutions for sucrose and D-mannitol were problematic. In particular, Escherichia coli BW25113 is a K-12 strain (closely related to MG1655) and should not be able to grow on sucrose. In M9 media made with our original stock solution of sucrose, E. coli BW25113 grew, but in media made with a fresh stock solution, it did not. Similarly, growth of E. coli on mannitol should require the phosphotransferase uptake protein mtlA and the dehydrogenase mtlD. In our original fitness assays for E. coli, mtlA and mtlD were not important for growth on mannitol; instead, manX and manY, which encode the mannose phosphotransferase system, were important. When we repeated these experiments with a fresh stock solution for D-mannitol, we found that mtlA and mtlD were important for fitness, and manX and manY were not.<br>Please disregard the data regarding sucrose or D-mannitol. In the Fitness Browser (https://fit.genomics.lbl.gov), the problematic fitness experiments have been removed. As of September 2021, the data for these compounds in the Fitness Browser is from fresh stock solutions of sucrose and D-mannitol. We also checked that the data from these experiments is consistent with prior knowledge of the utilization of these compounds. Finally, we checked the gene re-annotations that were related to these sucrose or mannitol utilization.<br>