cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14615016
title: Supplementary Material from Logical modelling of <i>in vitro</i> differentiation of human monocytes into dendritic cells unravels novel transcriptional regulatory interactions

description: Dendritic cells (DCs) are the major specialized antigen-presenting cells, thereby connecting innate and adaptive immunity. Because of their role in establishing adaptive immunity, they constitute promising targets for immunotherapy. Monocytes can differentiate into DCs <i>in vitro</i> in the presence of colony-stimulating factor 2 (CSF2) and interleukin 4 (IL4), activating four signalling pathways (MAPK, JAK/STAT, NFKB and PI3 K). However, the downstream transcriptional program responsible for DC differentiation from monocytes (moDC) remains unknown. By analysing the scientific literature on moDC differentiation, we established a preliminary logical model that helped us identify missing information regarding the activation of genes responsible for this differentiation, including missing targets for key transcription factors (TFs). Using ChIP-seq and RNA-seq data from the Blueprint consortium, we defined active, and inactive promoters, together with differentially expressed genes in monocytes, moDCs and macrophages, which correspond to an alternative cell fate. We then used this functional genomic information to predict novel targets for previously identified TFs. By integrating this information, we refined our model and recapitulated the main established facts regarding moDC differentiation. Prospectively, the resulting model should be useful to develop novel immunotherapies targeting moDCs.
DOI: 10.6073/pasta/fa2bddf212a86ca5663c8d958e73e2fc
title: Long-term Hydrographic Mooring Data from the Georgia Coastal Ecosystems LTER Salinity Monitoring Program - Primary 30 Minute Observational Data

description: Conductivity, temperature and sub-surface water pressure were measured continuously at fixed hydrographic moorings distributed across the Georgia Coastal Ecosystems LTER study area to document spatial and temporal variability of salinity and its relationship to water level and river discharge. Mooring locations were chosen to span the salinity gradient as well as to take advantage of existing physical infrastructure (e.g. docks or pilings) for mounting instruments and proximity to marsh study sites. Eight moorings were established between 2001 and 2003 to characterize salinity patterns in the three primary sounds in the GCE domain (Sapelo, Doboy and Altamaha), and a ninth mooring was added near a freshwater tidal forest along the Altamaha River in 2014. Observations were logged at 30 minute intervals by Sea-Bird Electronics MicroCAT 37-SM data loggers and downloaded approximately quarterly. Salinity, depth and sigma-t (density anomaly) were calculated from the measured parameters using standard UNESCO algorithms, and short-duration gaps (&lt;6 hours) due to instrument swaps, quality control analysis or brief data interruptions were filled by interpolation. Long-duration gaps due to instrument or mooring loss were filled with null values to produce a monotonic time series. This data set includes cumulative 30 minute observations at all 9 moorings through 31-Dec-2019, and will be updated annually to include observations from the prior year.
DOI: 10.6084/m9.figshare.13550573
title: LLOMFTdataset

description: LLOM FT-ICR-MS formula assignment data supporting "Characterization of landfill leachate molecular composition using ultrahigh resolution mass spectrometry". ExperimentalIonMass is averaged m/z from matrix generation, elemental composition (H, C, O, N, S, P, Cl, Br, and F) is for protonated corresponding formula assignments, and signal intensities in sample triplicates are counts in arbitrary units. The dataset was filtered for m/z ions that appeared in all triplicate extracts but signal intensities have not been averaged across triplicates in this data.
DOI: 10.6084/m9.figshare.13550573.v1
title: LLOMFTdataset

description: LLOM FT-ICR-MS formula assignment data supporting "Characterization of landfill leachate molecular composition using ultrahigh resolution mass spectrometry". ExperimentalIonMass is averaged m/z from matrix generation, elemental composition (H, C, O, N, S, P, Cl, Br, and F) is for protonated corresponding formula assignments, and signal intensities in sample triplicates are counts in arbitrary units. The dataset was filtered for m/z ions that appeared in all triplicate extracts but signal intensities have not been averaged across triplicates in this data.
DOI: 10.5281/zenodo.4766931
title: Understanding airspace in leaves: 3D anatomy and directional tortuosity

description: This dataset is presented in the following publication. Please cite this publication if you use the dataset. The accepted version can be accessed here:(https://onlinelibrary.wiley.com/share/author/DPQAQKKG2MNRS5KQEUAP?target=10.1111/pce.14079). Harwood, R., Théroux‐Rancourt, G. and Barbour, M.M. (2021), Understanding Airspace in Leaves: 3D Anatomy and Directional Tortuosity. Plant Cell Environ. Accepted Author Manuscript. [https://doi.org/10.1111/pce.14079]() <strong>Description of the dataset</strong> This dataset consists of scanning block face scanning electron microscopy (SBF-SEM) images of four anatomically contrasting Eucalyptus species, <em>E. grandis</em>, <em>E. camaldulensis</em>, <em>E. occidentalis</em>, and <em>E. parramattensis</em>. A single leaf was imaged for each species. More details on the imaging method can be found in Harwood et al. (2020). The following images are present for each species: <strong>SBFSEM</strong>: Raw micrograph. 8-bit grayscale image. <strong>Labels</strong>: Individual cells have been labelled, i.e. each have a single value, as well as other leaf tissues (e.g. epidermis, veins). The intercellular airspace has a single value. <strong>Cropped</strong>: The 'Labels' stack that was cropped to run a random walk analysis within the intercellular airspace. The the paper for further details on this method. <strong>Palisade</strong>, <strong>Adaxial/abaxial</strong> <strong>Palisade</strong>: An image stack cropped within the palisade mesophyll tissue. Some species had palisade tissue facing each epidermis and a substack was created for each. <strong>Spongy</strong>: An image stack cropped within the spongy mesophyll tissue. In all stacks, the leaves are oriented so that the adaxial epidermis (top of the leaf) is towards the top of the canvas, and the abaxial epidermis is towards the bottom of the canvas. The lateral orientation of the image in regards to the leaf lamina is unknown. For all species, the voxel depth is 50 nm. Voxel height and width is: <em>E. occidentalis</em>, <em>E. grandis</em> and<em> E. camaldulensis</em>: 90nm × 90nm <em>E. parramattensis</em>: 150nm × 150nm References Harwood, R., Goodman, E., Gudmundsdottir, M., Huynh, M., Musulin, Q., Song, M., & Barbour, M. M. (2020). Cell and chloroplast anatomical features are poorly estimated from 2D cross‐sections. New Phytologist, 225, 2567-2578. [https://doi.org/10.1111/nph.16219](https://doi.org/10.1111/nph.16219)
DOI: 10.5281/zenodo.4766930
title: Understanding airspace in leaves: 3D anatomy and directional tortuosity

description: This dataset is presented in the following publication. Please cite this publication if you use the dataset. The accepted version can be accessed here:(https://onlinelibrary.wiley.com/share/author/DPQAQKKG2MNRS5KQEUAP?target=10.1111/pce.14079). Harwood, R., Théroux‐Rancourt, G. and Barbour, M.M. (2021), Understanding Airspace in Leaves: 3D Anatomy and Directional Tortuosity. Plant Cell Environ. Accepted Author Manuscript. [https://doi.org/10.1111/pce.14079]() <strong>Description of the dataset</strong> This dataset consists of scanning block face scanning electron microscopy (SBF-SEM) images of four anatomically contrasting Eucalyptus species, <em>E. grandis</em>, <em>E. camaldulensis</em>, <em>E. occidentalis</em>, and <em>E. parramattensis</em>. A single leaf was imaged for each species. More details on the imaging method can be found in Harwood et al. (2020). The following images are present for each species: <strong>SBFSEM</strong>: Raw micrograph. 8-bit grayscale image. <strong>Labels</strong>: Individual cells have been labelled, i.e. each have a single value, as well as other leaf tissues (e.g. epidermis, veins). The intercellular airspace has a single value. <strong>Cropped</strong>: The 'Labels' stack that was cropped to run a random walk analysis within the intercellular airspace. The the paper for further details on this method. <strong>Palisade</strong>, <strong>Adaxial/abaxial</strong> <strong>Palisade</strong>: An image stack cropped within the palisade mesophyll tissue. Some species had palisade tissue facing each epidermis and a substack was created for each. <strong>Spongy</strong>: An image stack cropped within the spongy mesophyll tissue. In all stacks, the leaves are oriented so that the adaxial epidermis (top of the leaf) is towards the top of the canvas, and the abaxial epidermis is towards the bottom of the canvas. The lateral orientation of the image in regards to the leaf lamina is unknown. For all species, the voxel depth is 50 nm. Voxel height and width is: <em>E. occidentalis</em>, <em>E. grandis</em> and<em> E. camaldulensis</em>: 90nm × 90nm <em>E. parramattensis</em>: 150nm × 150nm References Harwood, R., Goodman, E., Gudmundsdottir, M., Huynh, M., Musulin, Q., Song, M., & Barbour, M. M. (2020). Cell and chloroplast anatomical features are poorly estimated from 2D cross‐sections. New Phytologist, 225, 2567-2578. [https://doi.org/10.1111/nph.16219](https://doi.org/10.1111/nph.16219)
DOI: 10.6084/m9.figshare.14615039
title: Supplemental File 2.xlsx from Glioblastoma multiforme: a multi-omics analysis of driver genes and tumour heterogeneity

description: Glioblastoma (GBM) is the most aggressive and common brain cancer in adults with the lowest life expectancy. The current neuro-oncology practice has incorporated genes involved in key molecular events that drive GBM tumorigenesis as biomarkers to guide diagnosis and design treatment. This study summarizes findings describing the significant heterogeneity of GBM at the transcriptional and genomic levels, emphasizing 18 driver genes with clinical relevance. A pattern was identified fitting the stem cell model for GBM ontogenesis, with an upregulation profile for <i>MGMT</i> and downregulation for <i>ATRX, H3F3A, TP53</i> and <i>EGFR</i> in the mesenchymal subtype. We also detected overexpression of <i>EGFR, NES, VIM</i> and <i>TP53</i> in the classical subtype and of <i>MKi67</i> and <i>OLIG2</i> genes in the proneural subtype. Furthermore, we found a combination of the four biomarkers <i>EGFR, NES, OLIG2</i> and <i>VIM</i> with a remarkable differential expression pattern which confers them a strong potential to determine the GBM molecular subtype. A unique distribution of somatic mutations was found for the young and adult population, particularly for genes related to DNA repair and chromatin remodelling, highlighting <i>ATRX, MGMT</i> and <i>IDH1.</i> Our results also revealed that highly lesioned genes undergo differential regulation with particular biological pathways for young patients. This multi-omic analysis will help delineate future strategies related to the use of these molecular markers for clinical decision-making in the medical routine.
DOI: 10.6084/m9.figshare.14615039.v1
title: Supplemental File 2.xlsx from Glioblastoma multiforme: a multi-omics analysis of driver genes and tumour heterogeneity

description: Glioblastoma (GBM) is the most aggressive and common brain cancer in adults with the lowest life expectancy. The current neuro-oncology practice has incorporated genes involved in key molecular events that drive GBM tumorigenesis as biomarkers to guide diagnosis and design treatment. This study summarizes findings describing the significant heterogeneity of GBM at the transcriptional and genomic levels, emphasizing 18 driver genes with clinical relevance. A pattern was identified fitting the stem cell model for GBM ontogenesis, with an upregulation profile for <i>MGMT</i> and downregulation for <i>ATRX, H3F3A, TP53</i> and <i>EGFR</i> in the mesenchymal subtype. We also detected overexpression of <i>EGFR, NES, VIM</i> and <i>TP53</i> in the classical subtype and of <i>MKi67</i> and <i>OLIG2</i> genes in the proneural subtype. Furthermore, we found a combination of the four biomarkers <i>EGFR, NES, OLIG2</i> and <i>VIM</i> with a remarkable differential expression pattern which confers them a strong potential to determine the GBM molecular subtype. A unique distribution of somatic mutations was found for the young and adult population, particularly for genes related to DNA repair and chromatin remodelling, highlighting <i>ATRX, MGMT</i> and <i>IDH1.</i> Our results also revealed that highly lesioned genes undergo differential regulation with particular biological pathways for young patients. This multi-omic analysis will help delineate future strategies related to the use of these molecular markers for clinical decision-making in the medical routine.
DOI: 10.6073/pasta/3df6c09ef42fd03901bdd3073d87425c
title: Long-term Hydrographic Mooring Data from the Georgia Coastal Ecosystems LTER Salinity Monitoring Program - Daily Summarized Data

description: Conductivity, temperature and sub-surface water pressure were measured continuously at fixed hydrographic moorings distributed across the Georgia Coastal Ecosystems LTER study area to document spatial and temporal variability of salinity and its relationship to water level and river discharge. Mooring locations were chosen to span the salinity gradient as well as to take advantage of existing physical infrastructure (e.g. docks or pilings) for mounting instruments and proximity to marsh study sites. Eight moorings were established between 2001 and 2003 to characterize salinity patterns in the three primary sounds in the GCE domain (Sapelo, Doboy and Altamaha), and a ninth mooring was added near a freshwater tidal forest along the Altamaha River in 2014. Observations were logged at 30 minute intervals by Sea-Bird Electronics MicroCAT 37-SM data loggers and downloaded approximately quarterly. Salinity, depth and sigma-t (density anomaly) were calculated from the measured parameters using standard UNESCO algorithms, and short-duration gaps (&lt;6 hours) due to instrument swaps, quality control analysis or brief data interruptions were filled by interpolation. Long-duration gaps due to instrument or mooring loss were filled with null values to produce a monotonic time series. Values flagged as invalid were then removed and interpolated up to 6 hours, and daily-summarized values were calculated by statistical aggregation. This data set includes the daily-summarized data at all 9 moorings through 31-Dec-2018, and will be updated annually to include observations from the prior year.
DOI: 10.6073/pasta/c9765bbc20e6026155f9bc0afe136da8
title: Disturbance to montioring plots at Atlamaha River Plant Transition Sites SCSA, ZSC1, and ZSC2 from 2013 to 2020.

description: We established permanent vegetation monitoring plots at Altamaha River plant transition sites in 2012. Starting in 2013, when we recorded plant sizes, we also noted any disturbance to the plots. Plots were scored as normal (no visible disturbance), disturbed by wrack (wrack present in plots and stems dead or broken), disturbed by snails (&gt;100 Littoraria per square meter and plant biomass low), disturbed by pigs (animal trail through the plot), initial slump (plot at the creekbank sliding into the creek based on movement of pvc poles or formation of a crevasse), and terminal slump (plot had slid far enough down that vegetation had drowned). Plots that experienced terminal slump or could not be found for any reason were scored as lost. Lost plots were replaced with a new plot in the same general area with the plot code incremented by 10. For example if plot 3 was lost, it was replaced by 13, and then in turn by 23.
DOI: 10.5281/zenodo.4771252
title: Dr.

description: The data for running models in the publication of "The link between ethnic diversity and scientific impact: the mediating effect of novelty and audience diversity".
DOI: 10.5281/zenodo.4771251
title: Dr.

description: The data for running models in the publication of "The link between ethnic diversity and scientific impact: the mediating effect of novelty and audience diversity".
DOI: 10.5281/zenodo.4771261
title: Observation water level, discharge and salinity gauge data in the Mekong Delta (2015)

description: Observed dry season (Feb-1<sup>st</sup> to April-15<sup>th</sup>) observed water level, discharge and salinity data in the Mekong Delta, received from the Southern Institute of Water Resources and Planning (SIWRP), Ho Chi Minh City, Vietnam. File name convention: STATION_NAME_obs_PROP; PROP = S for salinity, WL for water level, Q for discharge<br>
DOI: 10.5281/zenodo.4771260
title: Observation water level, discharge and salinity gauge data in the Mekong Delta (2015)

description: Observed dry season (Feb-1<sup>st</sup> to April-15<sup>th</sup>) observed water level, discharge and salinity data in the Mekong Delta, received from the Southern Institute of Water Resources and Planning (SIWRP), Ho Chi Minh City, Vietnam. File name convention: STATION_NAME_obs_PROP; PROP = S for salinity, WL for water level, Q for discharge<br>
DOI: 10.6084/m9.figshare.14615098
title: Supplementary material from Highly-connected, non-redundant microRNAs functional control in breast cancer molecular subtypes

description: Single ZIP file containing 8 supplementary files as described in the manuscript.
DOI: 10.6084/m9.figshare.14615102.v1
title: EmbryoNetworks from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Networks for each of the embyo develoment stages
DOI: 10.6084/m9.figshare.14615105
title: Supp_Mat_NetsInfo from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Information describing Networks used in the article
DOI: 10.6084/m9.figshare.14615111
title: Supp_Mat_LoTo_Embryo from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Detailed results of the comaprison between networks
DOI: 10.6084/m9.figshare.14615105.v1
title: Supp_Mat_NetsInfo from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Information describing Networks used in the article
DOI: 10.6084/m9.figshare.14615102
title: EmbryoNetworks from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Networks for each of the embyo develoment stages
DOI: 10.6084/m9.figshare.14615099.v1
title: Supp_Mat_GO from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Gene Onthology annotation of differentialy regulated genes
DOI: 10.6084/m9.figshare.14615111.v1
title: Supp_Mat_LoTo_Embryo from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Detailed results of the comaprison between networks
DOI: 10.6084/m9.figshare.14615114
title: F1-05_networks from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Cytoscape session with subnetworks of nodes with largest variations between embryo stages
DOI: 10.6084/m9.figshare.14615114.v1
title: F1-05_networks from Automated generation of context-specific gene regulatory networks with a weighted approach in <i>Drosophila melanogaster</i>

description: Cytoscape session with subnetworks of nodes with largest variations between embryo stages
DOI: 10.5281/zenodo.3763348
title: Data-LIS

description: This data package is used to test let-it-snow (LIS) software installation version 1.8. LIS source code is available in the projet repository: https://gitlab.orfeo-toolbox.org/remote_modules/let-it-snow/ Data package structure (do not modify these folders).<br> - Baseline : Baseline data folder. It contains output files of LIS that have been reviewed and validated.<br> - Data-Test : Test data folder needed to run tests. It contains Landsat, Take5 and SRTM data.<br> - Output-Test : Temporary output tests folder. This package supersedes the previous package (https://doi.org/10.5281/zenodo.166511) that was used to test LIS 1.5.
DOI: 10.5281/zenodo.3763349
title: Data-LIS 1.6

description: This data package is used to test let-it-snow (LIS) software installation version 1.6. LIS source code is available in the projet repository: https://gitlab.orfeo-toolbox.org/remote_modules/let-it-snow/ Data package structure (do not modify these folders).<br> - Baseline : Baseline data folder. It contains output files of LIS that have been reviewed and validated.<br> - Data-Test : Test data folder needed to run tests. It contains Landsat, Take5 and SRTM data.<br> - Output-Test : Temporary output tests folder. This package supersedes the previous package (https://doi.org/10.5281/zenodo.166511) that was used to test LIS 1.5.
DOI: 10.5281/zenodo.5846826
title: Data-LIS

description: This data package is used to test let-it-snow (LIS) software installation version 1.6 and 1.7. LIS source code is available in the projet repository: https://gitlab.orfeo-toolbox.org/remote_modules/let-it-snow/ Data package structure (do not modify these folders).<br> - Baseline : Baseline data folder. It contains output files of LIS that have been reviewed and validated.<br> - Data-Test : Test data folder needed to run tests. It contains Landsat, Take5 and SRTM data.<br> - Output-Test : Temporary output tests folder. This package supersedes the previous package (https://doi.org/10.5281/zenodo.166511) that was used to test LIS 1.5.
DOI: 10.5281/zenodo.7352173
title: Data-LIS

description: This data package is used to test let-it-snow (LIS) software installation version 1.8. LIS source code is available in the projet repository: https://gitlab.orfeo-toolbox.org/remote_modules/let-it-snow/ Data package structure (do not modify these folders).<br> - Baseline : Baseline data folder. It contains output files of LIS that have been reviewed and validated.<br> - Data-Test : Test data folder needed to run tests. It contains Landsat, Take5 and SRTM data.<br> - Output-Test : Temporary output tests folder. This package supersedes the previous package (https://doi.org/10.5281/zenodo.166511) that was used to test LIS 1.5.
DOI: 10.5281/zenodo.7352058
title: Microelectrode register (MER) data from Deep Brain Stimulation (DBS) surgery in Parkinson's disease patients

description: MER data consist of brain signal in different depths when DBS surgery is being done. In each depth, a data file is created, with different duration depending on the depth, and up to three channels. Data come from 14 patients (9 males and 5 females), they are anonymized and labelled from P1 to P14. They correspond to patients in age 65.1 +- 5.6 years. Data are organized in STN-IN and STN-OUT (different depths in each folder), subthalamus-in, and subthalamus-out since the STN area is the target area when implanting a DBS. Classification in STN-IN and STN-OUT was made by the neurophysiologists and surgeons. Data were recorded for left and right lobes, 8 patients in left and right lobe, 1 patient in right lobe, and 5 patients in left lobe. The format is mat file (MATLAB file) Data sampling frequency is 12kHz. No filtering or data processing was made, they are directly obtained from the MER acquisition system.