cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29071346.v1
title: <b>Shared and distinctive microbial biomarkers enhance precision diagnostics of inflammatory bowel disease and its subtypes</b>

description: Inflammatory Bowel Disease (IBD) is a chronic inflammatory gut disease with major subtypes of Crohn's disease (CD) and ulcerative colitis (UC). They significantly differ in pathology but are similar in clinical manifestations, bringing considerable challenges for accurate non-invasive diagnosis. Recent research highlights the gut microbiome as a promising physiological indicator for diverse diseases, prompting us to investigate shared or distinctive microbial species insights into IBD and its subtypes. For this purpose, we initially established a standardized computational workflow to identify gut microbial biomarkers and their patterns for IBD diagnosis and subtype discrimination. In the process, 1,210 metagenomic samples were analyzed from 6 cohorts; among them, 81 shared species were identified (18 enriched, 63 depleted) across both CD and UC, whereas CD harbored 73 distinct species (37 enriched, 36 depleted) and UC had 32 distinct species (19 enriched, 13 depleted). Functional profiling illustrated shared and distinctive enriched MetaCyc pathways across the two subtypes, offering a comprehensive view of subtype-specific metabolic pathways. Finally, a two-stage machine learning framework was built for diagnosis and subtyping of IBD, making IBD identification in the first stage and subtype classification in the second stage. The framework was well-trained and achieved considerable accuracy, even leading to a novel discovery that shared microbes dominate IBD diagnosis, while distinct microbes drive subtype discrimination.
DOI: 10.6084/m9.figshare.8956997.v1
title: Peruvian Scientific Journal Titles in Emerging Sources Citation Index-Web of Science (June-2019)

description: Data is part current research around a thesis degree in Spanish intitled "Calidad editorial, impacto científico y visibilidad web de las revistas científicas de universidades peruanas". Incluye general metrics about 22 scientific and scholary journal published by universities and other editorial types indexing at Emerging Sources Citation Index (WoS) updated on June, 2019.
DOI: 10.6084/m9.figshare.5447167.v1
title: datasets

description: This folder contains datasets to be downloaded from students for their practices with R and Python<br>
DOI: 10.6084/m9.figshare.22696291.v4
title: Freemocap Test Data

description: Test data and calibration file for the Freemocap motion capture software. Data is at a very low frame rate to reduce size. Should only be used for testing functionality, not inspecting output.
DOI: 10.6084/m9.figshare.19350668.v1
title: Tourism.csv

description: This dataset contains data for tourism company
DOI: 10.6084/m9.figshare.12095496.v1
title: Sample Metadata

description: Metadata information for Winogradsky column 16S sequencing samples
DOI: 10.6084/m9.figshare.21383679.v1
title: Stock Price Data of 12 New Energy Companies

description: The data of paper.
DOI: 10.6084/m9.figshare.26242070.v2
title: Cluster dataset

description: Data of jobs run in Cluster A and Cluster-B
DOI: 10.6084/m9.figshare.3827010.v1
title: NegDDI_DrugBank.zip

description: NegDDI_DrugBank Corpus
DOI: 10.6084/m9.figshare.23337092.v1
title: The known and predicted transposons of four mosquitos (<em>Anopheles albimanus</em>, <em>Anopheles colluzzii</em>, <em>Aedes aegypti</em> and <em>Culex quinquefasciatus</em>).

description: The known and predicted transposons of four mosquitos (<em>Anopheles albimanus</em>, <em>Anopheles colluzzii</em>, <em>Aedes aegypti</em> and <em>Culex quinquefasciatus</em>), that were used for the annotation of the genomes. The detailed description of how these files were prepared and the results of the genomic annotation are described in the paper: ...
DOI: 10.4121/14743263.v1
title: Data underlying the paper: Using agent-based simulation for emergent behavior detection in cyber-physical systems

description: The dataset contains a collection of experiment results and event logs generated. The experiments comprise a logistics case study involving the transport of products that are subject to quality depreciation. The products are transported on smart pallets, which enables us to keep track of various measures (e.g., location, quality depreciation level, etc.). We considered the problem as a special case of the dynamic pickup and delivery problem in which objects need to be transported between an origin and a destination. The case study is implemented in a discrete-event simulation model. This dataset contains the experiment input (i.e., input parameters) and results (i.e., simulation output files and filtered output files considering the removal of a warm-up period). As output, we also provide event logs, which could, for example, be used for model verification or process mining purposes.
DOI: 10.6084/m9.figshare.5101135.v3
title: Euonymus europaeus chorology

description: Distribution map of spindle (<i>Euonymus europaeus</i>)<br><br>These maps were produced by combining numerous and heterogeneous data collected from atlas monographs providing complete species distribution maps, from national to regional atlases, occurrence geo-databases, scientific and grey literature.<br>The maps were created using ESRI shapefiles (*.shp, *.shx, *.dbf, *.prj files) archived in the ZIP file. Species range is mapped with polygon features (name suffix "plg"), which define continuous areas of occupancy of the species, and with point features (name suffix "pnt"), which identify more fragmented and isolated populations. If synanthropic occurrences are reported outside the species natural range, additional point and/or polygon shapefiles are also present (suffix "syn"). <br>Polygon borders delimiting species ranges are generalized across the mainland and sea boundaries. This offers the possibility to mask sea areas or to clip and extract the terrestrial range parts using GIS data layers of the users' choice. An additional version of polygon ranges are clipped with a coastline (name suffix "clip"), which have been derived from Natural Earth dataset "Admin 0 - Countries" 1:50M version 4.1.0 (https://www.naturalearthdata.com). <br><br>Please cite as:<br>Caudullo, G., Welk, E., San-Miguel-Ayanz, J., 2017. Chorological maps for the main European woody species. Data in Brief 12, 662-666. DOI: doi.org/10.1016/j.dib.2017.05.007 <br><br>Additional information and used references are on 'supplementary materials' document:<br>https://doi.org/10.6084/m9.figshare.5091901<br><br>Chorological maps are part of the "European Atlas of Forest Tree Species" project:<br>https://w3id.org/mtv/FISE-Comm/v01
DOI: 10.6084/m9.figshare.5121325.v1
title: Supplementary Material for: Cellular Scaling Rules for Primate Spinal Cords

description: The spinal cord can be considered a major sensorimotor interface between the body and the brain. How does the spinal cord scale with body and brain mass, and how are its numbers of neurons related to the number of neurons in the brain across species of different body and brain sizes? Here we determine the cellular composition of the spinal cord in eight primate species and find that its number of neurons varies as a linear function of cord length, and accompanies body mass raised to an exponent close to 1/3. This relationship suggests that the extension, mass and number of neurons that compose the spinal cord are related to body length, rather than to body mass or surface. Moreover, we show that although brain mass increases linearly with cord mass, the number of neurons in the brain increases with the number of neurons in the spinal cord raised to the power of 1.7. This faster addition of neurons to the brain than to the spinal cord is consistent with current views on how larger brains add complexity to the processing of environmental and somatic information.
DOI: 10.6084/m9.figshare.956247.v1
title: Gaussian Job Archive for C6H6Br2

description: Archive of work produced using the resources of the Imperial College High Performance Computing Service.
DOI: 10.4121/20814784.v1
title: Supporting information: "Chenier Formation Through Wave Winnowing and Tides"

description: This dataset accompanies the paper entitled, "Chenier Formation Through Wave Winnowing and Tides", published in the Journal of Geophysical Research: Earth Surface. The Delft3D model input files used in this study have been included here as supporting information. One of the 28 scenarios modelled has been included here (the scenario shown in Figure 1), the model files of all scenarios are identical except for the boundary conditions (waves and water level), the MorFac (morphological acceleration factor, which was scaled inversely to the wave height) and the run duration. These files were run with Delft3D-FLOW version 4.00.04.757 and Delft3D-WAVE version 3.04.01.757 to produce the results shown in this paper. Details regarding the individual file types can be found in the Delft3D User Manual.
DOI: 10.6084/m9.figshare.29169692.v1
title: ST_mel1_rep2

description: Data analyzed in BayesSpace paper (https://www.nature.com/articles/s41587-021-00935-2).
DOI: 10.6084/m9.figshare.20485716.v2
title: Pymatgen PatchedPhaseDiagrams

description: Patched phase diagram covering a large number of chemical systems (all the ones in Materials Project and WBM dataset put together) as well as the ComputedStructureEntry queried from MPRester to generate it. <br> PPDs were generated in this file: https://github.com/janosh/dielectric-frontier/blob/314fb478/diel_frontier/patched_phase_diagram/combine_mp_wbm_ppd.py <br> Load e.g. the Jan 2022 MP+WBM PPD using <br> ```py import gzip<br> import io<br> import pickle<br> from urllib.request import urlopen<br> <br> # 2022-01-25-ppd-mp+wbm.pkl.gz (235 MB)<br> ppd_pickle_url = "https://figshare.com/ndownloader/files/36669624"<br> zipped_file = urlopen(ppd_pickle_url)<br> ppd_mp_wbm = pickle.load(io.BytesIO(gzip.decompress(zipped_file.read()))) ```
DOI: 10.6084/m9.figshare.5688811.v3
title: Twitter Death Hoaxes dataset

description: This is a dataset of death reports collected from Twitter between 1st January, 2012 and 31st December, 2014. It was collected by tracking the keyword 'RIP', and matching those tweets in which a name is mentioned next to RIP. Matching names were identified by using Wikidata as a database of names. For more details, please refer to the paper:https://arxiv.org/abs/1801.07311<br><br>The dataset contains 4,007 death reports, of which 2,301 are real deaths, 1,092 are commemorations and 614 are fake deaths.<br>Along with this dataset, the word embeddings models used in this paper are also provided.<br>This dataset is released in accordance with Twitter's TOS, which allows sharing of tweet IDs and are intended for non-commercial research.<br>Note: Twitter's developer policy doesn't allow sharing more than 1,500,000 tweet IDs (https://dev.twitter.com/overview/terms/policy#updated-policy), unless the author is affiliated with an academic institution (which is my case) and tweet IDs are solely used for non-commercial purposes (https://twittercommunity.com/t/policy-update-clarification-research-use-cases/87566). Hence, by downloading these datasets you agree that you will not use it for commercial purposes.
DOI: 10.6084/m9.figshare.25460671.v1
title: simulateddata_21to24.tar.gz

description: This archive contains simulated genotype data. There are 4 distinct simulation scenarios, each with 10 replicate simulated datasets. Each simulated dataset contains genotypes from 10,000 SNPs and 1,000 families. More detailed information about each simulation scenario is available in the README file contained in the archive. This is a companion data set to https://figshare.com/articles/dataset/simulated_data_tar_gz/22041074.
DOI: 10.6084/m9.figshare.28232987.v1
title: Size-Dependent Growth and Mortality Models for Japanese Tree Species

description: This is an interdisciplinary data set, including longevity Indices and climate data for Japanese tree species. Please refer to Kobayashi and Akasaka, ####### for details on data collection and processing.Supplementary Data 1: Potential maximum diameter of 87 tree species. Supplementary Data 2: Life table from age 0 to the potential maximum lifespan at 1 cm diameter for 53 tree species. Supplementary Data 3: Longevity indices for 53 tree species. Supplementary Data 4: Diameter data of Carpinus laxiflora in natural forests. Supplementary Data 5: Tree monitoring data of Carpinus laxiflora across all forest types. Supplementary Code 1: R script for calculating longevity indices. Supplementary Code 2: R script for statistical analysis of the main results.
DOI: 10.6084/m9.figshare.22138019.v1
title: The course of women’s emotions from early pregnancy to postpartum period

description: This study aims to examine typical patterns and stability of emotions (including positive emotions) in low-risk, healthy pregnant and postpartum women. Participants completed a series of self-report measures at eight time points: 7.6 ± 1.2 gestational weeks (gw) (denotad as “T1_” in the table), 10.3 ± 0.8 gw (denotad as “T2_”), 13.5 ± 1.4 gw (denotad as “T3_”), 20.4 ± 1.6 gw (denotad as “T4_”), 30.4 ± 1.2 gw (denotad as “T5_”), 34.7 ± 1.2 gw (denotad as “T6_”); 0.4 ± 0.2 (denotad as “T7_”) and 7.6 ± 2.9 (denotad as “T8_”) weeks postpartum. At baseline, participants provided information about their sociodemographic background. At each time point, they completed questionnaires assessing positive and negative emotions (PANAS), perceived stress (EPDS), depressive symptoms (PSS), and anxiety (STAI). Data related to perinatal outcomes (birth weight, Apgar score) and child sex were collected via questionnaires administered in the early postpartum period. A total of 176 women were recruited. In line with study aims, only women with typical, low-risk pregnancy, no psychiatric treatment and favorable perinatal outcomes were included in the analysis. We excluded the participants with miscarriage (n=12), in vitro fertilization (IVF) (n=7), low Apgar score at 5 min (&lt; 8) and/or low birth weight (&lt; 2500 grams) (n=6). The final data set included 151 participants.
DOI: 10.6084/m9.figshare.27929355.v2
title: Data raw

description: All numerial values that were used to generate grahs,histogram
DOI: 10.6084/m9.figshare.28686089.v1
title: Supporting data for "Thorax temperature and niche characteristics as predictors of abundance of Amazonian Odonata"

description: This is the supporting data for the above manuscript
DOI: 10.6084/m9.figshare.14396273.v1
title: Supplemental Table S5

description: Supplemental Table S5 for "Keeping up with the <i>Bacillus cereus </i>group: taxonomy through the genomics era and beyond"
DOI: 10.6084/m9.figshare.26129863.v1
title: Training dataset

description: This file contains the training dataset used to train the machine learning model. It includes a wide range of features combined to create a robust training set for model development.
DOI: 10.6084/m9.figshare.7814186.v4
title: random media meshes

description: FEM triangular mesh with random polydisperse spherical exclusions<br>
DOI: 10.6084/m9.figshare.13685839.v2
title: Carbon Monitor: Global daily CO2 emissions from fossil fuel combustion and cement production 2020

description: <i>Carbon Monitor is a near real-time dataset for daily CO2 emissions with global coverage from 6 main sectors (power, industry, ground transportation, aviation, residential and international shipping).</i><br><i>Here, we provide the whole year data of 2019 and 2020.<br>Visit our website for more information: <i>https://carbonmonitor.org</i></i>
DOI: 10.6084/m9.figshare.23296082.v1
title: Data and Code for "Reassessment of growth-climate relations indicates the potential for decline across Eurasian boreal larch forests".

description: Data and Code used in the paper "Reassessment of growth-climate relations indicates the potential for decline across Eurasian boreal larch forests".
DOI: 10.6084/m9.figshare.6728255.v1
title: Sunspots - Monthly Activity since 1749

description: Sunspots - Monthly Activity since 1749
DOI: 10.6084/m9.figshare.28147505.v1
title: Two migratory rice pest occurrence ratio anomalies of south China from 1996 to 2016(provincial scale)

description: This dataset describes the occurrence ratio anomalies of two migratory pests at the provincial scale for the main rice-producing province in southern China, from 1996 to 2016. The original data were obtained from the Statistical Yearbook of National Specialised Plant Protection.
DOI: 10.6084/m9.figshare.12235409.v1
title: Depression Tasks.xlsx

description: These tasks were formulated to help people suffering from depression, as a part of my final year research project.
DOI: 10.6084/m9.figshare.7297373.v1
title: Address lookups

description: Address Lookup<br>Field description<br>sender_address masked input (sender) Bitcoin addresses of the transaction<br>transaction_id Bitcoin transaction identifier
DOI: 10.15468/dl.75hxav
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Holtbyrnia innesi (Fowler, 1934)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((9.7509 37.8496,8.9648 37.5879,8.9648 28.8496,17.9648 28.8496,17.9648 31.4107,15.9933 31.8399,15.7087 32.5876,15.3783 32.8575,13.447 33.3951,12.448 33.3201,11.5958 33.6971,11.3566 34.2292,11.7126 34.4306,11.838 34.8337,11.4958 36.0284,11.2722 36.2509,11.6203 36.7533,11.5006 37.3226,11.1934 37.5676,10.5795 37.5806,9.7509 37.8496))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013508-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.25288213.v1
title: IMPEDANCE DATA

description: Impedance data for hybrid nanoparticle-DNAzyme biosensor for non-faradaic impedimetric detection of heavy metal ions.
DOI: 10.6084/m9.figshare.11944875.v1
title: Replication Package "Dynamically Reconfiguring Software Microbenchmarks: Reducing Execution Time Without Sacrificing Result Quality"

description: This is the replication package for the ESEC/FSE 2020 paper "Dynamically Reconfiguring Software Microbenchmarks: Reducing Execution Time Without Sacrificing Result Quality".<br>A pre-print of the paper is available at https://t.uzh.ch/13k.<br>
DOI: 10.6084/m9.figshare.7564187.v1
title: Additional file 4: of Artificial association of memory events by optogenetic stimulation of hippocampal CA3 cell ensembles

description: Input-output function. Data of input-output function obtained from KA1::Cre and CA3-NR1 KO mice infected with AAV-EF1α::DIO-ChR2-mCherry in the CA3 region. Laser power and fEPSP amplitude at the time of getting maximum fEPSP amplitude and at the time of using 50% of this stimulation intensity are shown. There was no statistical difference of input-output function between the groups (50% stimulation intensity, unpaired Student’s t test; t6 = 0.6807, p = 0.5214; 100% stimulation intensity, unpaired Student’s t test; t6 = 0.8144, p = 0.4465; 50% fEPSP amplitude, unpaired Student’s t test; t6 = 0.6289, p = 0.5526; 100% fEPSP amplitude, t6 = 0.7006, p = 0.5098). (XLS 27 kb)
DOI: 10.6084/m9.figshare.5634745
title: The use of tools to support oral lesion description in oral medicine referrals

description: Abstract: Poor description of oral lesions jeopardize the prioritization of appointments in Oral Medicine. The present study investigated whether the use of support tools changes the quality of descriptions focusing on health care prioritization. Two oral lesions (A and B) were described by 64 dental students and 48 dentists using three methods: (a) without support tools (free); (b) using the oral examination form from the Specialties Manual in Oral Health/Brazilian Ministry of Health (SMOH form); and (c) using the OralDESC guideline. The descriptions were compared with a gold standard and percentage of agreement was analyzed by the Kruskal-Wallis and Dunn's tests (p&lt;0.05). Descriptions with the OralDESC presented higher information quality. Considering items essential for prioritization, the OralDESC demonstrated better performance for lesion A; for lesion B, free descriptions and descriptions using the OralDESC were of higher quality than those using SMOH form. Therefore, the OralDESC offered greater support for the description of oral lesions for health care prioritization in Oral Medicine.
DOI: 10.6084/m9.figshare.23834538.v1
title: MIBlood-EV_v1_template.pdf

description: The MIBlood-EV v1.0 includes 27 items the following components: i) General study information (items 1.0 – 1.9), ii) Blood collection and processing (items 2.0 – 2.23), and iii) Plasma/serum quality control (QC; items 3.0 – 3.27)The MIBlood-EV can facilitate peer review of blood EV studies and interpretation and reproducibility of research findings. The MIBlood-EV will be accessible on the ISEV website under Rigor & Standardization Subcommittee/Position Papers & Guidelines alongside the MIFlowCyt-EV https://www.isev.org/rigor-standardization.The original version (v1.0) is an editable pdf document that can be attached as Supplementary Material in manuscripts and referred to in sections of the Materials and Methods that describe blood specimens and characteristics. In addition, researchers are invited to upload the MIBlood-EV in the dedicated figshare data repository (here). <b>The file name should be as follows:</b><b> </b><b>First Author Last Name_First Author First Name_Year of Publication.</b><br>
DOI: 10.6084/m9.figshare.29061038.v2
title: Datasets used in Transitive prediction of small-molecule function through alignment of high-content screening resources

description: This dataset supports the development of CLIP<sup>n</sup>, a contrastive-learning framework designed to align heterogeneous high-content screening (HCS) profile datasets.<br>GitHub link: https://github.com/AltschulerWu-Lab/CLIPn<br>Directory Structure<br>Foldersraw_profilesHCS13/Contains raw data from 13 high-content screening (HCS) datasets. Each dataset includes meta and feature files.<br>L1000/CDRP_feature_exp.csv: Raw L1000 expression data from the CDRP dataset.CDRP_meta_exp.csv: Metadata associated with the CDRP expression data.LINCS_feature_exp.csv: Raw L1000 expression data from the LINCS dataset.LINCS_meta_exp.csv: Metadata associated with the LINCS expression data.<br>RxRx3/RxRx3_feature_final.csv: Profile data from the RxRx3 dataset.RxRx3_meta_final.csv: Metadata from the RxRx3 dataset.<br>Uncharacterized_compounds/NCI_cpnData.csv: Feature data for uncharacterized compounds from the NCI dataset.NCI_cpnInfo.csv: Information about uncharacterized compounds in the NCI dataset.Prestwick_UTSW_cpnData.csv: Feature data for uncharacterized compounds from the Prestwick UTSW dataset.Prestwick_UTSW_cpnInfo.csv: Information about uncharacterized compounds from the Prestwick UTSW dataset.<br><br>Data ReferenceFor raw datasets from 13 HCS database, data and analysis pipeline for dataset 1 was obtained from https://www.science.org/doi/suppl/10.1126/science.1100709/suppl_file/perlman.som.zip; for datasets 2-3, data were shared by authors; For datasets 4-5, analysis code was downloaded from https://static-content.springer.com/esm/art:10.1038/nbt.3419/MediaObjects/41587_2016_BFnbt3419_MOESM21_ESM.zip and data were shared by authors; For datasets 6-7, processed dataset was downloaded from AWS following instructions from https://github.com/carpenter-singh-lab/2022_Haghighi_NatureMethods, and replicate_level_cp_normalized.csv.gz features were used. For project datasets 8-13, datasets and analysis results were downloaded from https://zenodo.org/records/7352487. For RxRx3, dataset was obtained from https://www.rxrx.ai/rxrx3. L1000 transcript datasets were downloaded using the same link as datasets 6-7 and the processed transcript data files (named “replicate_level_l1k.csv”) were used.