cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive154595.20201210.5
title: Streptococcus sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive154596.20201210.5
title: Aggregatibacter segnis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive154597.20201210.5
title: Ruminococcus gnavus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive154598.20201210.5
title: Stenotrophomonas maltophilia

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive154599.20201210.5
title: Mycobacterium mucogenicum

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive154600.20201210.5
title: Eggerthella lenta

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15468/dl.xgud98
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Citrus ×natsudaidai (Yu.Tanaka) Hayata"
 ]
}

 The dataset includes 49 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091799-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.34e92z
title: Occurrence Download

description: A dataset containing 257604 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cichorium intybus L."
 ]
}

 The dataset includes 257604 records from 1933 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091768-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57778/wqdc-q670
title: Downscaled and bias corrected dataset for multiple GCMs and variables 

description: Understanding the impact of climate variability and change is of great importance for developing adaptation and mitigation strategies. Coarse resolution data sets such as simulations of general circulation models (GCMs) are important for reconstructing historical climate and predicting the future. However, scale discrepancy and biases limit the coarse resolution data sets from being directly used for impact assessments and decision making. One solution for bridging this gap is to downscale and bias correct coarse resolution data to the local scale.
description: We bias corrected and downscaled 9 climate variables for 5 popular GCMs from the latest CMIP6 with a widly used method, namely quantile delta mapping (QDM). The dataset has spatial resolution of 0.25 degree and daily temporal scale. For each GCM, two emission levels are included(ssp126 as low emission level and ssp585 as high emission level). The names of the 5 GCMs are EC-Earth3, MPI-ESM1-2-HR, MRI-ESM2-0, IPSL-CM6A-LR,and GFDL-ESM4. The 9 variables include daily total precipitation (pr), daily maximum near-surface air temperature(tasmax), daily minimum near-surface air temperature (tasmin),eastward near-surface wind (uas),northward near-surface wind (vas),near-surface relative humidity (hurs), surface downwelling shortwave radiation (rsds), surface downwelling longwave radiation (rlds) and sea level pressure (psl). The dataset will be used as forcings for the watershed modeling and physical/biogeochemical modeling around the bay area to explore adaptation and mitigation strategies.
DOI: 10.35078/biygoa
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Varginha | Município: Perdões

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.35078/nattgr
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Montes Claros | Município: Riacho dos Machados

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.25345/c5b56df4b
title: MassIVE MSV000091920 - SPERM CHROMATIN STRUCTURE AND REPRODUCTIVE FITNESS ARE ALTERED BY SUBSTITUTION OF A SINGLE AMINO ACID IN MOUSE PROTAMINE 1
title: Quantification of histone PTMs from mouse sperm chromatin.
DOI: 10.6084/m9.figshare.22803527
title: Atlanta Crime Incidents 2015-2020.csv

description: Crime incident data from Atlanta, GA from 2015-2020
DOI: 10.5517/ccdc.csd.cc27zs12
title: CCDC 2085154: Experimental Crystal Structure Determination

description: Related Article: Hannes Michaels, Matthias J. Golomb, Byeong Jo Kim, Tomas Edvinsson, Fabio Cucinotta, Paul G. Waddell, Michael R. Probert, Steven J. Konezny, Gerrit Boschloo, Aron Walsh, Marina Freitag|2022|J.Mater.Chem.A|10|9582|doi:10.1039/D2TA00267A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27zs23
title: CCDC 2085155: Experimental Crystal Structure Determination

description: Related Article: Hannes Michaels, Matthias J. Golomb, Byeong Jo Kim, Tomas Edvinsson, Fabio Cucinotta, Paul G. Waddell, Michael R. Probert, Steven J. Konezny, Gerrit Boschloo, Aron Walsh, Marina Freitag|2022|J.Mater.Chem.A|10|9582|doi:10.1039/D2TA00267A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5519/qd.0x3ml0zi
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.57745/4kyanb
title: Species_data.tab

description: :unav
DOI: 10.57745/aflvvq
title: Woodland_data.tab

description: :unav
DOI: 10.57745/axfwvm
title: Matched_Landscapes_data.tab

description: :unav
DOI: 10.57745/rmzovu
title: CerealField_data.tab

description: :unav
DOI: 10.57745/ytlwbt
title: ReadME.zip

description: :unav
DOI: 10.57745/qhbesr
title: MUESLI_Tortosaetal_2023.Rmd

description: :unav
DOI: 10.6084/m9.figshare.22802888
title: FateMap Paper datasets #2 (Goyal et al., 2021, Biorxiv)

description: Datasets from: https://www.biorxiv.org/content/10.1101/2021.12.08.471833v1.full FM01: BRAF-mutant melanoma WM989 treated with vemurafenib FM02: BRAF-mutant melanoma WM989 treated with vemurafenib, trametenib and their combination (provided here) FM03: BRAF-mutant melanoma WM989 treated with vemurafenib, including pre-treatment with DOT1Li (provided here) FM04: Breast Cancer MDA-MB-231 treated with paclitaxel FM05: BRAF-mutant melanoma WM983B treated with vemurafenib FM06: BRAF-mutant melanoma WM989 untreated FM07: BRAF-mutant melanoma WM989 treated with vemurafenib (continuous and discontinuous) FM08: Primary human melanocytes (provided here) FM09: NRAS-mutant melanoma 3451 treated with trametinib FM10: NRAS-mutant melanoma 3623 treated with trametinib <br> We have also provided all processed files for all FMs and other FM's barcoded data are provided at the following DOI: 10.6084/m9.figshare.22798952
DOI: 10.6084/m9.figshare.22802888.v1
title: FateMap Paper datasets #2 (Goyal et al., 2021, Biorxiv)

description: Datasets from: https://www.biorxiv.org/content/10.1101/2021.12.08.471833v1.full FM01: BRAF-mutant melanoma WM989 treated with vemurafenib FM02: BRAF-mutant melanoma WM989 treated with vemurafenib, trametenib and their combination (provided here) FM03: BRAF-mutant melanoma WM989 treated with vemurafenib, including pre-treatment with DOT1Li (provided here) FM04: Breast Cancer MDA-MB-231 treated with paclitaxel FM05: BRAF-mutant melanoma WM983B treated with vemurafenib FM06: BRAF-mutant melanoma WM989 untreated FM07: BRAF-mutant melanoma WM989 treated with vemurafenib (continuous and discontinuous) FM08: Primary human melanocytes (provided here) FM09: NRAS-mutant melanoma 3451 treated with trametinib FM10: NRAS-mutant melanoma 3623 treated with trametinib <br> We have also provided all processed files for all FMs and other FM's barcoded data are provided at the following DOI: 10.6084/m9.figshare.22798952
DOI: 10.35078/99ktqy
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Varginha | Município: Piedade do Rio Grande

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.5517/ccdc.csd.cc2cp3w2
title: CCDC 2195044: Experimental Crystal Structure Determination

description: Related Article: Xiaoqi Tian, Kazutaka Shoyama, Bernhard Mahlmeister, Felix Brust, Matthias Stolte, Frank Würthner|2023|J.Am.Chem.Soc.|145|9886|doi:10.1021/jacs.3c03441
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cp3y4
title: CCDC 2195046: Experimental Crystal Structure Determination

description: Related Article: Xiaoqi Tian, Kazutaka Shoyama, Bernhard Mahlmeister, Felix Brust, Matthias Stolte, Frank Würthner|2023|J.Am.Chem.Soc.|145|9886|doi:10.1021/jacs.3c03441
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22289612
title: Updates on the study of lysosomal protein dynamics: possibilities for the clinic

description: The lysosome is the main degradative organelle of almost all mammalian cells, fulfilling important functions in macromolecule recycling, metabolism, and signaling. Lysosomal dysfunction is connected to a continuously growing number of pathologic conditions, and lysosomal proteins present potential biomarkers for a variety of diseases. Therefore, there is an increasing interest in their analysis in patient samples. We provide an overview of OMICs studies which identified lysosomal proteins as potential biomarkers for pathological conditions, covering proteomics, genomics, and transcriptomics approaches, identified through PubMed searches. With respect to discovery proteomics analyses, mainly lysosomal luminal and associated proteins were detected, while membrane proteins were found less frequently. Comprehensive coverage of the lysosomal proteome was only achieved by ultra-deep-coverage studies, but targeted approaches allowed for the reproducible quantification of lysosomal proteins in diverse sample types. The low abundance of lysosomal proteins complicates their reproducible analysis in patient samples. Whole proteome shotgun analyses fail in many instances to cover the lysosomal proteome, which is due to under-sampling and/or a lack of sensitivity. With the current state of the art, targeted proteomics assays provide the best performance for the characterization of lysosomal proteins in patient samples.
DOI: 10.6084/m9.figshare.22289612.v1
title: Updates on the study of lysosomal protein dynamics: possibilities for the clinic

description: The lysosome is the main degradative organelle of almost all mammalian cells, fulfilling important functions in macromolecule recycling, metabolism, and signaling. Lysosomal dysfunction is connected to a continuously growing number of pathologic conditions, and lysosomal proteins present potential biomarkers for a variety of diseases. Therefore, there is an increasing interest in their analysis in patient samples. We provide an overview of OMICs studies which identified lysosomal proteins as potential biomarkers for pathological conditions, covering proteomics, genomics, and transcriptomics approaches, identified through PubMed searches. With respect to discovery proteomics analyses, mainly lysosomal luminal and associated proteins were detected, while membrane proteins were found less frequently. Comprehensive coverage of the lysosomal proteome was only achieved by ultra-deep-coverage studies, but targeted approaches allowed for the reproducible quantification of lysosomal proteins in diverse sample types. The low abundance of lysosomal proteins complicates their reproducible analysis in patient samples. Whole proteome shotgun analyses fail in many instances to cover the lysosomal proteome, which is due to under-sampling and/or a lack of sensitivity. With the current state of the art, targeted proteomics assays provide the best performance for the characterization of lysosomal proteins in patient samples.
DOI: 10.6084/m9.figshare.22568154
title: Data-independent acquisition mass spectrometry reveals comprehensive plasma protein profiles in the natural history of patients with hereditary transthyretin amyloidosis (ATTRv)

description: Hereditary transthyretin amyloidosis (ATTRv) is a rare, fatal, autosomal dominant disease with more than 140 mutations discovered. Three phenotypes of amyloid infiltration are neuropathy (ATTRv-PN), cardiopathy (ATTRv-CM), and neuropathy + cardiopathy (ATTRv-MIX). The lack of ATTR-specific biomarkers, difficulties in biopsy evidence, and limited known pathogenic mechanisms have made diagnosis difficult. Newly emerging noninvasive measures for monitoring progression and disease-modifying therapies have improved early diagnosis and patient management. Our research applies the latest technology, Data-Independent Acquisition-Based Quantitative Proteomics (DIA), to reveal comprehensive plasma protein profiles in the natural history of Chinese patients with hereditary transthyretin amyloidosis (ATTRv). We analyzed differentially expressed proteins (DEPs) in three phenotypes (ATTRv-PN, ATTRv-CM, and ATTRv-MIX). Serum samples were collected from a total of 18 patients (6 ATTRv-PN, 5 ATTRv-CM, and 7 ATTRv-MIX patients) and 20 healthy participants as a control group. Combined with the results of the proteomic and bioinformatic analyses, we found 30 DEPs and protein interaction networks clustered in KRT family proteins and DSC3 between ATTRv-PN and the control, which were rich in the estrogen signaling pathway and the cell adhesion molecule (CAM) pathway. This study demonstrates a global and significant proteomic profile in different stages of ATTRv.
DOI: 10.6084/m9.figshare.22568154.v1
title: Data-independent acquisition mass spectrometry reveals comprehensive plasma protein profiles in the natural history of patients with hereditary transthyretin amyloidosis (ATTRv)

description: Hereditary transthyretin amyloidosis (ATTRv) is a rare, fatal, autosomal dominant disease with more than 140 mutations discovered. Three phenotypes of amyloid infiltration are neuropathy (ATTRv-PN), cardiopathy (ATTRv-CM), and neuropathy + cardiopathy (ATTRv-MIX). The lack of ATTR-specific biomarkers, difficulties in biopsy evidence, and limited known pathogenic mechanisms have made diagnosis difficult. Newly emerging noninvasive measures for monitoring progression and disease-modifying therapies have improved early diagnosis and patient management. Our research applies the latest technology, Data-Independent Acquisition-Based Quantitative Proteomics (DIA), to reveal comprehensive plasma protein profiles in the natural history of Chinese patients with hereditary transthyretin amyloidosis (ATTRv). We analyzed differentially expressed proteins (DEPs) in three phenotypes (ATTRv-PN, ATTRv-CM, and ATTRv-MIX). Serum samples were collected from a total of 18 patients (6 ATTRv-PN, 5 ATTRv-CM, and 7 ATTRv-MIX patients) and 20 healthy participants as a control group. Combined with the results of the proteomic and bioinformatic analyses, we found 30 DEPs and protein interaction networks clustered in KRT family proteins and DSC3 between ATTRv-PN and the control, which were rich in the estrogen signaling pathway and the cell adhesion molecule (CAM) pathway. This study demonstrates a global and significant proteomic profile in different stages of ATTRv.
DOI: 10.35078/xfyamo
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Varginha | Município: Pedra do Indaiá

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.5281/zenodo.5187910
title: Hand-BCG & SCG signals dataset

description: <strong>General description</strong> This repository contains Ballistocardiogram signals collected from multiple users while they were holding a mobile phone in hand and Seismocardiogram signals collected with the phone placed on their chest. It consists of 3 different datasets made up of multiple recordings from a total of 272 different users. The main characteristics of these datasets are given below. +---------------+-------------+-------------+-----------------+------------------------------+-----------------------+--------------------+------------+-----------+<br> | | Loc. | # users | Age range | # sessions per user | session length | Phone | Acc. Fs | Gyr. Fs |<br> +---------------+-------------+-------------+-----------------+------------------------------+-----------------------+--------------------+------------+-----------+<br> | Dataset A | Hand | 112 | 20-60 | 10 | 30s | Samsung S8 | 100 Hz | 500 Hz |<br> +---------------+-------------+-------------+-----------------+------------------------------+-----------------------+--------------------+------------+-----------+<br> | Dataset B | Hand | 105 | 20-32 | 1 | 30s | Google Pixel | 50 Hz | 400 Hz |<br> +---------------+-------------+-------------+-----------------+------------------------------+-----------------------+--------------------+------------+-----------+<br> | Dataset C | Chest | 55 | 19-52 | 4 | 30s | Google Pixel | 50 Hz | 400 Hz |<br> +---------------+-------------+-------------+-----------------+------------------------------+-----------------------+--------------------+------------+-----------+ <strong>Content of each dataset</strong> Each dataset is made up of multiple files, with each file corresponding to a given measurement session. The name of a given file indicates some metadata about the measurement session itselft. It is assigned based on the following template: &lt;UserId&gt;-&lt;Gender&gt;-&lt;Age&gt;yrs-&lt;SignalLength&gt;_&lt;Year&gt;-&lt;Month&gt;-&lt;Day&gt;:&lt;Hour&gt;-&lt;Minute&gt;-&lt;Second&gt;.csv The content of the file itself corresponds to the sensor readings collected during the measurement session. It is a collection of timestamped sensor values, reported in a comma-separated format. The first column represent the timestamp of the sensor event (in nanoseconds), the second one the type of the considered sensor and the 3 following ones the actual values along the different axis. Please refer to the official Android SensorEvent documentation for more details.