100+ datasets found
  1. n

    Data from: HmtDB - Human Mitochondrial DataBase

    • neuinfo.org
    • dknet.org
    • +1more
    Updated Feb 14, 2025
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    (2025). HmtDB - Human Mitochondrial DataBase [Dataset]. http://identifiers.org/RRID:SCR_007713
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    Dataset updated
    Feb 14, 2025
    Description

    A human mitochondrial resource aimed at supporting population genetics and mitochondrial disease studies. It consists of a database of Human Mitochondrial Genomes annotated with population and variability data, the latter estimated through the application of a new approach based on site-specific nucleotidic and aminoacidic variability calculation (SiteVar and MitVarProt programs). The goals of HmtDB are: to collect and integrate the publicly available human mitochondrial genomes data; to produce and provide the scientific community with site-specific nucleotidic and aminoacidic variability data estimated on all the collected human mitochondrial genome sequences; to allow any researcher to analyse his own human mitochondrial sequences (both complete and partial mitochondrial genomes) in order to automatically detect the nucleotidic variants compared to the revised Cambridge Reference Sequence (rCRS) and to predict their haplogroup paternity. HmtDBs first release contains 1255 human mitochondrial genomes derived from public databases (GenBank and MitoKor). The genomes have been stored and analysed as a whole dataset and grouped in continent-specific subsets (AF: Africa, AM: America, AS: Asia, EU: Europe, OC: Oceania). :The multialignment and site-variability analysis tools included in HmtDB are clustered in two Work Flows: the Variability Generation Work Flow (VGWF) and the Classification Work Flow (CWF), which are applied both to human mitochondrial genomes stored in the database and to newly sequenced genomes submitted by the user, respectively.

  2. Global Human Settlement - Urban Centres Database

    • hub.arcgis.com
    Updated Sep 16, 2020
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    Esri Deutschland (2020). Global Human Settlement - Urban Centres Database [Dataset]. https://hub.arcgis.com/datasets/2344906dc4a04c748b690b9a92c8446c
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    Dataset updated
    Sep 16, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Deutschland
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Pacific Ocean, North Pacific Ocean
    Description

    The Global Human Settlement Layer Urban Centres Database (GHS-UCDB) is the most complete database on cities to date, publicly released as an open and free dataset - GHS STAT UCDB2015MT GLOBE R2019A. The database represents the global status on Urban Centres in 2015 by offering cities location, their extent (surface, shape), and describing each city with a set of geographical, socio-economic and environmental attributes, many of them going back 25 or even 40 years in time. Urban Centres are defined in a consistent way across geographical locations and over time, applying the “Global Definition of Cities and Settlements” developed by the European Union to the Global Human Settlement Layer Built-up (GHS-BUILT) areas and Population (GHS-POP) grids. This report contains the description of the dimensions and the derived attributes that characterise the Urban Centres in the database. The document includes notes about methodology and sources. The GHS-UCDB contains information for more than 10,000 Urban Centres and it is the baseline data of the analytical results presented in the Atlas of the Human Planet.https://publications.jrc.ec.europa.eu/repository/bitstream/JRC115586/ghs_stat_ucdb2015mt_globe_r2019a_v1_0_web_1.pdfViews of this layer are used in web maps for the ArcGIS Living Atlas of the World.

  3. d

    Real-Time Verified Search Fund Data | 200mm US Records | Personal Emails &...

    • datarade.ai
    .csv, .xls
    Updated Jul 23, 2024
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    Wiza (2024). Real-Time Verified Search Fund Data | 200mm US Records | Personal Emails & 100mm Mobile Phone Numbers | Live-Sourced Linkedin Data [Dataset]. https://datarade.ai/data-products/wiza-real-time-verified-search-fund-data-200mm-us-records-wiza
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    .csv, .xlsAvailable download formats
    Dataset updated
    Jul 23, 2024
    Dataset authored and provided by
    Wiza
    Area covered
    United States
    Description

    Stop relying on outdated and inaccurate databases and let Wiza be your source of truth for all deal sourcing and founder / CEO outreach.

    Why we're different: The search fund market is dynamic and competitive - Wiza is not a static financial database that gets refreshed on occasion. Every datapoint is sourced and verified the moment that you receive the information. We verify deliverability of every single email ahead of providing the data, and we ensure that each person in your dataset has 100% job title and company accuracy by leveraging Linkedin Data sourced through their live Linkedin profile.

    Key Features:

    Comprehensive Data Coverage: Stop contacting the same people as everyone else. Wiza's search fund Data is sourced live, not stored in a limited database. When you tell us the type of company or person you would like to contact, we leverage Linkedin Data (the largest, most accurate database in the world) to find everyone who matches your ICP, and then we source the contact data and company data in real-time.

    High-Quality, Accurate Data: Wiza ensures accuracy of all datapoints by taking a few key steps that other data providers fail to take: (1) Every email is SMTP verified ahead of delivery, ensuring they will not bounce (2) Every person's Linkedin profile is checked live to ensure we have 100% job title, company, location, etc. accuracy, ahead of providing any data (3) Phone numbers are constantly being verified with AI to ensure accuracy

    Linkedin Data: Wiza is able to provide Linkedin Data points, sourced live from each person's Linkedin profile, including Subtitle, Bio, Job Title, Job Description, Skills, Languages, Certifications, Work History, Education, Open to Work, Premium Status, and more!

    Personal Data: Wiza has access to industry leading volumes of B2C Contact Data, meaning you can find gmail/yahoo/hotmail email addresses, and mobile phone number data to contact your potential partners.

  4. n

    Human Mortality Database

    • neuinfo.org
    • dknet.org
    • +2more
    Updated Mar 22, 2025
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    (2025). Human Mortality Database [Dataset]. http://identifiers.org/RRID:SCR_002370
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    Dataset updated
    Mar 22, 2025
    Description

    A database providing detailed mortality and population data to those interested in the history of human longevity. For each country, the database includes calculated death rates and life tables by age, time, and sex, along with all of the raw data (vital statistics, census counts, population estimates) used in computing these quantities. Data are presented in a variety of formats with regard to age groups and time periods. The main goal of the database is to document the longevity revolution of the modern era and to facilitate research into its causes and consequences. New data series is continually added to this collection. However, the database is limited by design to populations where death registration and census data are virtually complete, since this type of information is required for the uniform method used to reconstruct historical data series. As a result, the countries and areas included are relatively wealthy and for the most part highly industrialized. The database replaces an earlier NIA-funded project, known as the Berkeley Mortality Database. * Dates of Study: 1751-present * Study Features: Longitudinal, International * Sample Size: 37 countries or areas

  5. Data from: Global terrorism database

    • kaggle.com
    zip
    Updated Sep 14, 2018
    + more versions
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    Serif KAYA (2018). Global terrorism database [Dataset]. https://www.kaggle.com/datasets/serifkaya/global-terrorism-database
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    zip(27832583 bytes)Available download formats
    Dataset updated
    Sep 14, 2018
    Authors
    Serif KAYA
    Description

    Dataset

    This dataset was created by Serif KAYA

    Contents

  6. w

    Global Financial Inclusion (Global Findex) Database 2021 - Gabon

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Gabon [Dataset]. https://microdata.worldbank.org/index.php/catalog/4643
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    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Gabon
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Gabon is 1020.

    Mode of data collection

    Mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  7. r

    HIV-1 Human Protein Interaction Database

    • rrid.site
    • scicrunch.org
    • +1more
    Updated Feb 9, 2025
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    (2025). HIV-1 Human Protein Interaction Database [Dataset]. http://identifiers.org/RRID:SCR_006879
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    Dataset updated
    Feb 9, 2025
    Description

    A database of interactions between HIV-1 and human proteins published in the peer-reviewed literature. The goal is to provide a concise, yet detailed, summary of all known interactions of HIV-1 proteins with host cell proteins, other HIV-1 proteins, or proteins from disease organisms associated with HIV/AIDS. For each HIV-1 human protein interaction the following information is provided: * NCBI Reference Sequence (RefSeq) protein accession numbers. * NCBI Entrez Gene ID numbers. * Amino acids from each protein that are known to be involved in the interaction. * Brief description of the protein-protein interaction. * Keywords to support searching for interactions. * PubMed identification numbers (PMIDs) for all journal articles describing the interaction. In addition, all protein-protein interactions documented in the database are integrated into Entrez Gene records and listed in the ''HIV-1 protein interactions'' section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication.

  8. s

    Human Gene and Protein Database (HGPD)

    • scicrunch.org
    • neuinfo.org
    Updated Nov 23, 2008
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    (2008). Human Gene and Protein Database (HGPD) [Dataset]. http://identifiers.org/RRID:SCR_002889
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    Dataset updated
    Nov 23, 2008
    Description

    THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4,2023.The Human Gene and Protein Database presents SDS-PAGE patterns and other informations of human genes and proteins. The HGPD was constructed from full-length cDNAs. For conversion to Gateway entry clones, we first determined an open reading frame (ORF) region in each cDNA meeting the criteria. Those ORF regions were PCR-amplified utilizing selected resource cDNAs as templates. All the details of the construction and utilization of entry clones will be published elsewhere. Amino acid and nucleotide sequences of an ORF for each cDNA and sequence differences of Gateway entry clones from source cDNAs are presented in the GW: Gateway Summary window. Utilizing those clones with a very efficient cell-free protein synthesis system featuring wheat germ, we have produced a large number of human proteins in vitro. Expressed proteins were detected in almost all cases. Proteins in both total and supernatant fractions are shown in the PE: Protein Expression window. In addition, we have also successfully expressed proteins in HeLa cells and determined subcellular localizations of human proteins. These biological data are presented on the frame of cDNA clusters in the Human Gene and Protein Database. To build the basic frame of HGPD, sequences of FLJ full-length cDNAs and others deposited in public databases (Human ESTs, RefSeq, Ensembl, MGC, etc.) are assembled onto the genome sequences (NCBI Build 35 (UCSC hg17)). The majority of analysis data for cDNA sequences in HGPD are shared with the FLJ Human cDNA Database (http://flj.hinv.jp/) constructed as a human cDNA sequence analysis database focusing on mRNA varieties caused by variations in transcription start site (TSS) and splicing.

  9. w

    Consolidated Human Activities Database (CHAD)

    • data.wu.ac.at
    • catalog.data.gov
    • +1more
    Updated Jan 1, 2014
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    U.S. Environmental Protection Agency (2014). Consolidated Human Activities Database (CHAD) [Dataset]. https://data.wu.ac.at/odso/data_gov/NmE3NjAwYzctOTc0Yi00YTkzLWIwYjgtMTFjNDFiZTFjYWRh
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    Dataset updated
    Jan 1, 2014
    Dataset provided by
    U.S. Environmental Protection Agency
    Area covered
    bc433b691eb83a32860504082a84631a15b815d0
    Description

    The Consolidated Human Activity Database (CHAD) contains data obtained from human activity studies that were collected at city, state, and national levels. CHAD is intended to be an input file for exposure/intake dose modeling and/or statistical analysis.

  10. National Address Database

    • hub.arcgis.com
    • resilience-fema.hub.arcgis.com
    • +3more
    Updated Apr 7, 2022
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    Esri U.S. Federal Datasets (2022). National Address Database [Dataset]. https://hub.arcgis.com/maps/fedmaps::national-address-database-1/about
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    Dataset updated
    Apr 7, 2022
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    National Address DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a U.S. Department of Transportation (USDOT) feature layer, displays address data in the United States. Per USDOT, "The U.S. Department of Transportation (USDOT) and its partners from all levels of government recognize the need for a National Address Database (NAD). Accurate and up-to-date addresses are critical to transportation safety and are a vital part of Next Generation 9-1-1. They are also essential for a broad range of government services, including mail delivery, permitting, and school siting. To meet this need, USDOT partners with address programs from state, local, and tribal governments to compile their authoritative data into the NAD."District of Columbia (DC) Residential AddressesData currency: Current federal service (Address Points from National Address Database)NGDAID: 196 (National Address Database (NAD))For more information: Getting to know the National Address Database (NAD); National Address DatabaseFor feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

  11. National DNA Database statistics

    • gov.uk
    Updated Jan 14, 2025
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    Home Office (2025). National DNA Database statistics [Dataset]. https://www.gov.uk/government/statistics/national-dna-database-statistics
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    Dataset updated
    Jan 14, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Home Office
    Description

    These statistics include:

    • crime matches
    • subject samples
    • NDNAD breakdown
    • gender
    • ethnic appearance
    • age

    We are currently unable to provide figures on matches made against profiles on the National DNA Database.

    https://webarchive.nationalarchives.gov.uk/20200702201509/https://www.gov.uk/government/statistics/national-dna-database-statistics" class="govuk-link">Statistics from Q1 2013 to Q4 2018 to 2019 are available on the National Archives.

    Please note that figures for Q2 2014 to 2015 are unavailable. This is due to technical issues with the management information system.

  12. d

    National Database for Clinical Trials Related to Mental Illness (NDCT)

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Jul 26, 2023
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    National Institutes of Health (NIH) (2023). National Database for Clinical Trials Related to Mental Illness (NDCT) [Dataset]. https://catalog.data.gov/dataset/national-database-for-clinical-trials-related-to-mental-illness-ndct
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    Dataset updated
    Jul 26, 2023
    Dataset provided by
    National Institutes of Health (NIH)
    Description

    The National Database for Clinical Trials Related to Mental Illness (NDCT) is an extensible informatics platform for relevant data at all levels of biological and behavioral organization (molecules, genes, neural tissue, behavioral, social and environmental interactions) and for all data types (text, numeric, image, time series, etc.) related to clinical trials funded by the National Institute of Mental Health. Sharing data, associated tools, methodologies and results, rather than just summaries or interpretations, accelerates research progress. Community-wide sharing requires common data definitions and standards, as well as comprehensive and coherent informatics approaches for the sharing of de-identified human subject research data. Built on the National Database for Autism Research (NDAR) informatics platform, NDCT provides a comprehensive data sharing platform for NIMH grantees supporting clinical trials.

  13. Synthetic Human Model Dataset for Skeleton Driven Non-rigid Motion Tracking...

    • data.csiro.au
    • researchdata.edu.au
    • +1more
    Updated Jan 24, 2019
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    Shafeeq Elanattil; Peyman Moghadam (2019). Synthetic Human Model Dataset for Skeleton Driven Non-rigid Motion Tracking and 3D Reconstruction [Dataset]. http://doi.org/10.25919/5c495488b0f4e
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    Dataset updated
    Jan 24, 2019
    Dataset provided by
    CSIROhttp://www.csiro.au/
    Authors
    Shafeeq Elanattil; Peyman Moghadam
    License

    https://research.csiro.au/dap/licences/csiro-data-licence/https://research.csiro.au/dap/licences/csiro-data-licence/

    Dataset funded by
    CSIROhttp://www.csiro.au/
    Queensland University of Technology
    Description

    We introduce a synthetic dataset for evaluating non-rigid 3D human reconstruction based on conventional RGB-D cameras. The dataset consist of seven motion sequences of different actions of a single human model. For each motion sequence per-frame ground truth geometry of the human model and ground truth skeleton are given. The dataset also contains skinning weights of the human model. Detailed documentation js available in the https://research.csiro.au/robotics/our-work/databases/synthetic-human-model-dataset/

  14. d

    Georeferenced Population Datasets of Mexico (GEO-MEX): Population Database...

    • catalog.data.gov
    • s.cnmilf.com
    • +6more
    Updated Dec 6, 2023
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    SEDAC (2023). Georeferenced Population Datasets of Mexico (GEO-MEX): Population Database of Mexico [Dataset]. https://catalog.data.gov/dataset/georeferenced-population-datasets-of-mexico-geo-mex-population-database-of-mexico
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    Dataset updated
    Dec 6, 2023
    Dataset provided by
    SEDAC
    Area covered
    Mexico
    Description

    The Population Database of Mexico contains geographically referenced population data for Mexican states, municipalities and localities from the 1990 Mexican population and housing census. The data include population by gender and age group for approximately 83.7% of the Mexican population. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

  15. US Clinical Trials Data Package

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). US Clinical Trials Data Package [Dataset]. https://www.johnsnowlabs.com/marketplace/us-clinical-trials-data-package/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Description

    This data package contains datasets on clinical trials conducted in the United States. Diseases include cervical cancer, diabetes, acute respiratory infection as well as stress. This data package also includes clinical trials registry and results database.

  16. Berkeley Multimodal Human Action Database

    • kaggle.com
    Updated Feb 4, 2020
    + more versions
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    dasmehdixtr (2020). Berkeley Multimodal Human Action Database [Dataset]. https://www.kaggle.com/dasmehdixtr/berkeley-multimodal-human-action-database/notebooks
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 4, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    dasmehdixtr
    Description

    The Berkeley Multimodal Human Action Database (MHAD) contains 11 actions performed by 7 male and 5 female subjects in the range 23-30 years of age except for one elderly subject. All the subjects performed 5 repetitions of each action, yielding about 660 action sequences which correspond to about 82 minutes of total recording time. In addition, we have recorded a T-pose for each subject which can be used for the skeleton extraction; and the background data (with and without the chair used in some of the activities). Figure 1 shows the snapshots from all the actions taken by the front-facing camera and the corresponding point clouds extracted from the Kinect data. The specified set of actions comprises of the following: (1) actions with movement in both upper and lower extremities, e.g., jumping in place, jumping jacks, throwing, etc., (2) actions with high dynamics in upper extremities, e.g., waving hands, clapping hands, etc. and (3) actions with high dynamics in lower extremities, e.g., sit down, stand up. Prior to each recording, the subjects were given instructions on what action to perform; however no specific details were given on how the action should be executed (i.e., performance style or speed). The subjects have thus incorporated different styles in performing some of the actions (e.g., punching, throwing). Figure 2 shows a snapshot of the throwing action from the reference camera of each camera cluster and from the two Kinect cameras. The figure demonstrates the amount of information that can be obtained from multi-view and depth observations as compared to a single viewpoint.

    For more info, please visit this.

    The Actions are: 1- Jumping in place 2- Jumping jacks 3- Bending 4- Punching 5- Waving(two hands) 6- Waving(one hand) 7- Clapping Hands 9- Throwing a ball 10- Sit Down 11- Stand Up 12- T-Pose

  17. w

    Global Financial Inclusion (Global Findex) Database 2017 - Afghanistan,...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 13, 2022
    + more versions
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    Global Financial Inclusion (Global Findex) Database 2017 - Afghanistan, Albania, Algeria...and 133 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/3324
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    Dataset updated
    Jun 13, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2017
    Area covered
    Afghanistan, Albania, Algeria...and 133 more
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    See Methodology document for country-specific geographic coverage details.

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world’s population (see Table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used.

    Respondents are randomly selected within the selected households. Each eligible household member is listed and the handheld survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer’s gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Mode of data collection

    Other [oth]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

    Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

  18. d

    Database of Genotype and Phenotype (dbGaP)

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Feb 3, 2025
    + more versions
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    National Library of Medicine (2025). Database of Genotype and Phenotype (dbGaP) [Dataset]. https://catalog.data.gov/dataset/database-of-genotype-and-phenotype-dbgap
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    National Library of Medicine
    Description

    Database of Genotype and Phenotype (dbGaP) was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans.

  19. E

    EWA-DB – Early Warning of Alzheimer speech database

    • catalogue.elra.info
    • data.niaid.nih.gov
    • +1more
    Updated Oct 4, 2023
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    ELRA (European Language Resources Association) and its operational body ELDA (Evaluations and Language resources Distribution Agency) (2023). EWA-DB – Early Warning of Alzheimer speech database [Dataset]. https://catalogue.elra.info/en-us/repository/browse/ELRA-S0489/
    Explore at:
    Dataset updated
    Oct 4, 2023
    Dataset provided by
    ELRA (European Language Resources Association) and its operational body ELDA (Evaluations and Language resources Distribution Agency)
    ELRA (European Language Resources Association)
    License

    https://catalogue.elra.info/static/from_media/metashare/licences/ELRA_END_USER.pdfhttps://catalogue.elra.info/static/from_media/metashare/licences/ELRA_END_USER.pdf

    https://catalogue.elra.info/static/from_media/metashare/licences/ELRA_VAR.pdfhttps://catalogue.elra.info/static/from_media/metashare/licences/ELRA_VAR.pdf

    Description

    EWA-DB is a speech database that contains data from 3 clinical groups: Alzheimer's disease, Parkinson's disease, mild cognitive impairment, and a control group of healthy subjects. Speech samples of each clinical group were obtained using the EWA smartphone application, which contains 4 different language tasks: sustained vowel phonation, diadochokinesis, object and action naming (30 objects and 30 actions), picture description (two single pictures and three complex pictures).The total number of speakers in the database is 1649. Of these, there are 87 people with Alzheimer's disease, 175 people with Parkinson's disease, 62 people with mild cognitive impairment, 2 people with a mixed diagnosis of Alzheimer's + Parkinson's disease and 1323 healthy controls.For speakers who provided written consent (total number of 1003 speakers), we publish audio recordings in WAV format. We are also attaching a JSON file with ASR transcription, if available manual annotation (available for 965 speakers) and additional information about the speaker. For speakers who did not give their consent to publish the recording, only the JSON file is provided. ASR transcription is provided for all 1649 speakers. All 1649 speakers gave their consent to the provider to process their audio recordings. Therefore, it is possible for third party researchers to carry out their experiments also on the unpublished audio recordings through cooperation with the provider.

  20. UHPC Direct Tension Database

    • kaggle.com
    zip
    Updated Mar 17, 2024
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    Amjad Y Diab (2024). UHPC Direct Tension Database [Dataset]. https://www.kaggle.com/datasets/amjadydiab/uhpc-direct-tension-database/settings
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    zip(49489 bytes)Available download formats
    Dataset updated
    Mar 17, 2024
    Authors
    Amjad Y Diab
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Dataset

    This dataset was created by Amjad Y Diab

    Released under Apache 2.0

    Contents

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(2025). HmtDB - Human Mitochondrial DataBase [Dataset]. http://identifiers.org/RRID:SCR_007713

Data from: HmtDB - Human Mitochondrial DataBase

RRID:SCR_007713, nif-0000-02970, HmtDB - Human Mitochondrial DataBase (RRID:SCR_007713), HmtDB

Related Article
Explore at:
Dataset updated
Feb 14, 2025
Description

A human mitochondrial resource aimed at supporting population genetics and mitochondrial disease studies. It consists of a database of Human Mitochondrial Genomes annotated with population and variability data, the latter estimated through the application of a new approach based on site-specific nucleotidic and aminoacidic variability calculation (SiteVar and MitVarProt programs). The goals of HmtDB are: to collect and integrate the publicly available human mitochondrial genomes data; to produce and provide the scientific community with site-specific nucleotidic and aminoacidic variability data estimated on all the collected human mitochondrial genome sequences; to allow any researcher to analyse his own human mitochondrial sequences (both complete and partial mitochondrial genomes) in order to automatically detect the nucleotidic variants compared to the revised Cambridge Reference Sequence (rCRS) and to predict their haplogroup paternity. HmtDBs first release contains 1255 human mitochondrial genomes derived from public databases (GenBank and MitoKor). The genomes have been stored and analysed as a whole dataset and grouped in continent-specific subsets (AF: Africa, AM: America, AS: Asia, EU: Europe, OC: Oceania). :The multialignment and site-variability analysis tools included in HmtDB are clustered in two Work Flows: the Variability Generation Work Flow (VGWF) and the Classification Work Flow (CWF), which are applied both to human mitochondrial genomes stored in the database and to newly sequenced genomes submitted by the user, respectively.

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