100+ datasets found
  1. U.S. population data for human identification markers

    • catalog.data.gov
    Updated Jun 7, 2023
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    National Institute of Standards and Technology (2023). U.S. population data for human identification markers [Dataset]. https://catalog.data.gov/dataset/u-s-population-data-for-human-identification-markers
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    Dataset updated
    Jun 7, 2023
    Dataset provided by
    National Institute of Standards and Technologyhttp://www.nist.gov/
    Area covered
    United States
    Description

    The primary data consist of allele or haplotype frequencies for N=1036 anonymized U.S. population samples. Additional files are supplements to the associated publications. Any changes to spreadsheets are listed in the "Change Log" tab within each spreadsheet. DOI numbers for associated publications are listed below, under "References".

  2. d

    US Consumer Demographic Data - 269M+ Consumer Records - Programmatic Ads and...

    • datarade.ai
    Updated Jun 27, 2025
    + more versions
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    Giant Partners (2025). US Consumer Demographic Data - 269M+ Consumer Records - Programmatic Ads and Email Marketing Automation [Dataset]. https://datarade.ai/data-products/us-consumer-demographic-data-269m-consumer-records-progr-giant-partners
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Giant Partners
    Area covered
    United States of America
    Description

    Premium B2C Consumer Database - 269+ Million US Records

    Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

    Core Database Statistics

    Consumer Records: Over 269 million

    Email Addresses: Over 160 million (verified and deliverable)

    Phone Numbers: Over 76 million (mobile and landline)

    Mailing Addresses: Over 116,000,000 (NCOA processed)

    Geographic Coverage: Complete US (all 50 states)

    Compliance Status: CCPA compliant with consent management

    Targeting Categories Available

    Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

    Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

    Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

    Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

    Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

    Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

    Multi-Channel Campaign Applications

    Deploy across all major marketing channels:

    Email marketing and automation

    Social media advertising

    Search and display advertising (Google, YouTube)

    Direct mail and print campaigns

    Telemarketing and SMS campaigns

    Programmatic advertising platforms

    Data Quality & Sources

    Our consumer data aggregates from multiple verified sources:

    Public records and government databases

    Opt-in subscription services and registrations

    Purchase transaction data from retail partners

    Survey participation and research studies

    Online behavioral data (privacy compliant)

    Technical Delivery Options

    File Formats: CSV, Excel, JSON, XML formats available

    Delivery Methods: Secure FTP, API integration, direct download

    Processing: Real-time NCOA, email validation, phone verification

    Custom Selections: 1,000+ selectable demographic and behavioral attributes

    Minimum Orders: Flexible based on targeting complexity

    Unique Value Propositions

    Dual Spouse Targeting: Reach both household decision-makers for maximum impact

    Cross-Platform Integration: Seamless deployment to major ad platforms

    Real-Time Updates: Monthly data refreshes ensure maximum accuracy

    Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

    Compliance Management: Built-in opt-out and suppression list management

    Ideal Customer Profiles

    E-commerce retailers seeking customer acquisition

    Financial services companies targeting specific demographics

    Healthcare organizations with compliant marketing needs

    Automotive dealers and service providers

    Home improvement and real estate professionals

    Insurance companies and agents

    Subscription services and SaaS providers

    Performance Optimization Features

    Lookalike Modeling: Create audiences similar to your best customers

    Predictive Scoring: Identify high-value prospects using AI algorithms

    Campaign Attribution: Track performance across multiple touchpoints

    A/B Testing Support: Split audiences for campaign optimization

    Suppression Management: Automatic opt-out and DNC compliance

    Pricing & Volume Options

    Flexible pricing structures accommodate businesses of all sizes:

    Pay-per-record for small campaigns

    Volume discounts for large deployments

    Subscription models for ongoing campaigns

    Custom enterprise pricing for high-volume users

    Data Compliance & Privacy

    VIA.tools maintains industry-leading compliance standards:

    CCPA (California Consumer Privacy Act) compliant

    CAN-SPAM Act adherence for email marketing

    TCPA compliance for phone and SMS campaigns

    Regular privacy audits and data governance reviews

    Transparent opt-out and data deletion processes

    Getting Started

    Our data specialists work with you to:

    1. Define your target audience criteria

    2. Recommend optimal data selections

    3. Provide sample data for testing

    4. Configure delivery methods and formats

    5. Implement ongoing campaign optimization

    Why We Lead the Industry

    With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

    Contact our team to discuss your specific ta...

  3. n

    Data from: Estimating genome-wide heterozygosity: effects of demographic...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Sep 17, 2013
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    Joshua M. Miller; René M. Malenfant; Patrice David; Corey S. Davis; Jocelyn Poissant; John T. Hogg; Marco Festa-Bianchet; David W. Coltman (2013). Estimating genome-wide heterozygosity: effects of demographic history and marker type [Dataset]. http://doi.org/10.5061/dryad.6vk48
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    zipAvailable download formats
    Dataset updated
    Sep 17, 2013
    Dataset provided by
    University of Alberta
    Université de Sherbrooke
    Centre d'Écologie Fonctionnelle et Évolutive
    Montana Conservation Science Institute, Missoula, USA
    University of Sheffield
    Authors
    Joshua M. Miller; René M. Malenfant; Patrice David; Corey S. Davis; Jocelyn Poissant; John T. Hogg; Marco Festa-Bianchet; David W. Coltman
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Heterozygosity–fitness correlations (HFCs) are often used to link individual genetic variation to differences in fitness. However, most studies examining HFCs find weak or no correlations. Here, we derive broad theoretical predictions about how many loci are needed to adequately measure genomic heterozygosity assuming different levels of identity disequilibrium (ID), a proxy for inbreeding. We then evaluate the expected ability to detect HFCs using an empirical data set of 200 microsatellites and 412 single nucleotide polymorphisms (SNPs) genotyped in two populations of bighorn sheep (Ovis canadensis), with different demographic histories. In both populations, heterozygosity was significantly correlated across marker types, although the strength of the correlation was weaker in a native population compared with one founded via translocation and later supplemented with additional individuals. Despite being bi-allelic, SNPs had similar correlations to genome-wide heterozygosity as microsatellites in both populations. For both marker types, this association became stronger and less variable as more markers were considered. Both populations had significant levels of ID; however, estimates were an order of magnitude lower in the native population. As with heterozygosity, SNPs performed similarly to microsatellites, and precision and accuracy of the estimates of ID increased as more loci were considered. Although dependent on the demographic history of the population considered, these results illustrate that genome-wide heterozygosity, and therefore HFCs, are best measured by a large number of markers, a feat now more realistically accomplished with SNPs than microsatellites.

  4. f

    Individual subject level data.

    • figshare.com
    xlsx
    Updated May 27, 2025
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    Josh Poorbaugh; Jonathan T. Sims; Lin Zhang; Ching-Yun Chang; Richard E. Higgs; Ajay Nirula; Robert J. Benschop (2025). Individual subject level data. [Dataset]. http://doi.org/10.1371/journal.pone.0324242.s003
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    xlsxAvailable download formats
    Dataset updated
    May 27, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Josh Poorbaugh; Jonathan T. Sims; Lin Zhang; Ching-Yun Chang; Richard E. Higgs; Ajay Nirula; Robert J. Benschop
    License

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

    Description

    SARS-CoV-2 infections lead to a wide-range of outcomes from mild or asymptomatic illness to serious complications and death. While many studies have characterized hospitalized SARS-CoV-2 patient immune responses, we were interested in whether serious complications of SARS-CoV-2 infection could be predicted early in ambulatory subjects. To that end, we used samples from SARS-CoV-2-infected individuals from the placebo arm of the BLAZE-1 clinical trial who progressed to hospitalization or death compared to individuals in the same study who did not require medical intervention and investigated whether baseline serum cytokines and chemokines could predict severe outcome. High-risk demographic factors at baseline, including age, nasal pharyngeal viral load, duration from symptom onset, and BMI provide significant predictive capacity for a hospitalization or death with an AUC of ROC = 0.77. The predictive performance of our outcome modeling increased when baseline serum protein markers were included. In fact, the one-marker model indicated that there were 51 individual proteins (including known markers of inflammation like IL-6, MCP-3, CXCL10, IL-1Ra, and PTX3) that significantly increased the AUC of ROC beyond high-risk patient demographics alone to range between 0.78 to 0.88. Moreover, a two-marker model incorporating levels of both IL-6 and PTX3 further improved the prediction over the addition of a single protein marker to an AUC of ROC = 0.91. While the analytes identified in this study have been well-documented to be altered in SARS-CoV-2 infection, this analysis demonstrates the potential value of their use in predicting hospitalization or death in ambulatory participants infected with SARS-CoV-2 and could guide early treatment decisions.

  5. f

    Characteristics of study populations.

    • plos.figshare.com
    xls
    Updated May 27, 2025
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    Josh Poorbaugh; Jonathan T. Sims; Lin Zhang; Ching-Yun Chang; Richard E. Higgs; Ajay Nirula; Robert J. Benschop (2025). Characteristics of study populations. [Dataset]. http://doi.org/10.1371/journal.pone.0324242.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 27, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Josh Poorbaugh; Jonathan T. Sims; Lin Zhang; Ching-Yun Chang; Richard E. Higgs; Ajay Nirula; Robert J. Benschop
    License

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

    Description

    SARS-CoV-2 infections lead to a wide-range of outcomes from mild or asymptomatic illness to serious complications and death. While many studies have characterized hospitalized SARS-CoV-2 patient immune responses, we were interested in whether serious complications of SARS-CoV-2 infection could be predicted early in ambulatory subjects. To that end, we used samples from SARS-CoV-2-infected individuals from the placebo arm of the BLAZE-1 clinical trial who progressed to hospitalization or death compared to individuals in the same study who did not require medical intervention and investigated whether baseline serum cytokines and chemokines could predict severe outcome. High-risk demographic factors at baseline, including age, nasal pharyngeal viral load, duration from symptom onset, and BMI provide significant predictive capacity for a hospitalization or death with an AUC of ROC = 0.77. The predictive performance of our outcome modeling increased when baseline serum protein markers were included. In fact, the one-marker model indicated that there were 51 individual proteins (including known markers of inflammation like IL-6, MCP-3, CXCL10, IL-1Ra, and PTX3) that significantly increased the AUC of ROC beyond high-risk patient demographics alone to range between 0.78 to 0.88. Moreover, a two-marker model incorporating levels of both IL-6 and PTX3 further improved the prediction over the addition of a single protein marker to an AUC of ROC = 0.91. While the analytes identified in this study have been well-documented to be altered in SARS-CoV-2 infection, this analysis demonstrates the potential value of their use in predicting hospitalization or death in ambulatory participants infected with SARS-CoV-2 and could guide early treatment decisions.

  6. d

    Data from: Demographic histories shape population genomics of the common...

    • search.dataone.org
    • datadryad.org
    Updated Nov 29, 2023
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    S. D. Payet; M. S. Pratchett; P. Saenz-Agudelo; M. L. Berumen; J. D. DiBattista; H. B. Harrison (2023). Demographic histories shape population genomics of the common coral grouper (Plectropomus leopardus) [Dataset]. http://doi.org/10.5061/dryad.np5hqbzwv
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    Dataset updated
    Nov 29, 2023
    Dataset provided by
    Dryad Digital Repository
    Authors
    S. D. Payet; M. S. Pratchett; P. Saenz-Agudelo; M. L. Berumen; J. D. DiBattista; H. B. Harrison
    Time period covered
    Jan 1, 2022
    Description

    Many coral reef fishes display remarkable genetic and phenotypic variation across their geographic ranges. Understanding how historical and contemporary processes have shaped these patterns remains a focal question in evolutionary biology since they reveal how diversity is generated and how it may respond to future environmental change. Here we compare the population genomics and demographic histories of a commercially and ecologically important coral reef fish, the common coral grouper (Plectropomus leopardus [Lacépède 1802]), across two adjoining regions (the Great Barrier Reef; GBR, and the Coral Sea, Australia) spanning approximately 14 degrees of latitude and 9 degrees of longitude. We analysed 4,548 single nucleotide polymorphism (SNP) markers across 11 sites and show that genetic connectivity between regions is low, despite their relative proximity (~ 100 km) and an absence of any obvious geographic barrier. Inferred demographic histories using 10,479 markers suggest that the Cor..., , radiator_data_20220330_1452.vcf contains the dataset with neutral markers radiator_data_20220225_1456.vcf contains the dataset with outlier markers radiator_data_20220225_1927.vcf contains the dataset with markers used for demographic inference strata.filtered.tsv contains individual population metadata

    Filtering parameters and quality control are discussed in detail in Payet et al. (2022), Evolutionary Applications

  7. f

    Table_2_Genetic variation of endangered Jankowski’s Bunting (Emberiza...

    • frontiersin.figshare.com
    docx
    Updated Jun 7, 2023
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    Long Huang; Guochen Feng; Dan Li; Weiping Shang; Lishi Zhang; Rongfei Yan; Yunlei Jiang; Shi Li (2023). Table_2_Genetic variation of endangered Jankowski’s Bunting (Emberiza jankowskii): High connectivity and a moderate history of demographic decline.DOCX [Dataset]. http://doi.org/10.3389/fevo.2022.996617.s009
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    docxAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    Frontiers
    Authors
    Long Huang; Guochen Feng; Dan Li; Weiping Shang; Lishi Zhang; Rongfei Yan; Yunlei Jiang; Shi Li
    License

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

    Description

    IntroductionContinued discovery of “mismatch” patterns between population size and genetic diversity, involving wild species such as insects, amphibians, birds, mammals, and others, has raised issues about how population history, especially recent dynamics under human disturbance, affects currently standing genetic variation. Previous studies have revealed high genetic diversity in endangered Jankowski’s Bunting. However, it is unclear how the demographic history and recent habitat changes shape the genetic variation of Jankowski’s Bunting.MethodsTo explore the formation and maintenance of high genetic diversity in endangered Jankowski’s Bunting, we used a mitochondrial control region (partial mtDNA CR) and 15 nuclear microsatellite markers to explore the recent demographic history of Jankowski’s Bunting, and we compared the historical and contemporary gene flows between populations to reveal the impact of habitat change on population connectivity. Specifically, we aimed to test the following hypotheses: (1) Jankowski’s Bunting has a large historical Ne and a moderate demographic history; and (2) recent habitat change might have no significant impact on the species’ population connectivity.ResultsThe results suggested that large historical effective population size, as well as severe but slow population decline, may partially explain the high observable genetic diversity. Comparison of historical (over the past 4Ne generations) and contemporary (1–3 generations) gene flow indicated that the connectivity between five local populations was only marginally affected by landscape changes.DiscussionOur results suggest that high population connectivity and a moderate history of demographic decline are powerful explanations for the rich genetic variation in Jankowski’s Bunting. Although there is no evidence that the genetic health of Jankowski’s Bunting is threatened, the time-lag effects on the genetic response to recent environmental changes is a reminder to be cautious about the current genetic characteristics of this species. Where possible, factors influencing genetic variation should be integrated into a systematic framework for conducting robust population health assessments. Given the small contemporary population size, inbreeding, and ecological specialization, we recommend that habitat protection be maintained to maximize the genetic diversity and population connectivity of Jankowski’s Bunting.

  8. n

    Data from: Estimating relatedness and inbreeding using molecular markers and...

    • data.niaid.nih.gov
    • explore.openaire.eu
    • +3more
    zip
    Updated Sep 16, 2013
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    Stephen P. Robinson; Leigh W. Simmons; W. Jason Kennington (2013). Estimating relatedness and inbreeding using molecular markers and pedigrees: the effect of demographic history [Dataset]. http://doi.org/10.5061/dryad.060b1
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    zipAvailable download formats
    Dataset updated
    Sep 16, 2013
    Dataset provided by
    The University of Western Australia
    Authors
    Stephen P. Robinson; Leigh W. Simmons; W. Jason Kennington
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Margaret River, Western Australia, Australia, 33.95 °S, 115.07 °E
    Description

    Estimates of inbreeding and relatedness are commonly calculated using molecular markers, although the accuracy of such estimates has been questioned. As a further complication, in many situations, such estimates are required in populations with reduced genetic diversity, which is likely to affect their accuracy. We investigated the correlation between microsatellite- and pedigree-based coefficients of inbreeding and relatedness in laboratory populations of Drosophila melanogaster that had passed through bottlenecks to manipulate their genetic diversity. We also used simulations to predict expected correlations between marker- and pedigree-based estimates and to investigate the influence of linkage between loci and null alleles. Our empirical data showed lower correlations between marker- and pedigree-based estimates in our control (nonbottleneck) population than were predicted by our simulations or those found in similar studies. Correlations were weaker in bottleneck populations, confirming that extreme reductions in diversity can compromise the ability of molecular estimates to detect recent inbreeding events. However, this result was highly dependent on the strength of the bottleneck and we did not observe or predict any reduction in correlations in our population that went through a relatively severe bottleneck of N = 10 for one generation. Our results are therefore encouraging, as molecular estimates appeared robust to quite severe reductions in genetic diversity. It should also be remembered that pedigree-based estimates may not capture realized identity-by-decent and that marker-based estimates may actually be more useful in certain situations.

  9. Distribution of household population by infection marker

    • open.canada.ca
    • www150.statcan.gc.ca
    • +1more
    csv, html, xml
    Updated Jan 17, 2023
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    Statistics Canada (2023). Distribution of household population by infection marker [Dataset]. https://open.canada.ca/data/en/dataset/462433ae-22ef-4e07-b62d-93136c71f7ff
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    csv, xml, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Distribution of household population by infection marker, by sex and age group.

  10. g

    U.S. population data for human identification markers | gimi9.com

    • gimi9.com
    Updated Nov 14, 2020
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    (2020). U.S. population data for human identification markers | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_u-s-population-data-for-human-identification-markers
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    Dataset updated
    Nov 14, 2020
    Area covered
    United States
    Description

    The primary data consist of allele or haplotype frequencies for N=1036 anonymized U.S. population samples. Additional files are supplements to the associated publications. Any changes to spreadsheets are listed in the "Change Log" tab within each spreadsheet. DOI numbers for associated publications are listed below, under "References".

  11. f

    Population Genetic Structure and Demographic History of Atrina pectinata...

    • plos.figshare.com
    tiff
    Updated Jun 4, 2023
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    Dong-Xiu Xue; Hai-Yan Wang; Tao Zhang; Jin-Xian Liu (2023). Population Genetic Structure and Demographic History of Atrina pectinata Based on Mitochondrial DNA and Microsatellite Markers [Dataset]. http://doi.org/10.1371/journal.pone.0095436
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    tiffAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Dong-Xiu Xue; Hai-Yan Wang; Tao Zhang; Jin-Xian Liu
    License

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

    Description

    The pen shell, Atrina pectinata, is one of the commercial bivalves in East Asia and thought to be recently affected by anthropogenic pressure (habitat destruction and/or fishing pressure). Information on its population genetic structure is crucial for the conservation of A. pectinata. Considering its long pelagic larval duration and iteroparity with high fecundity, the genetic structure for A. pectinata could be expected to be weak at a fine scale. However, the unusual oceanography in the coasts of China and Korea suggests potential for restricted dispersal of pelagic larvae and geographical differentiation. In addition, environmental changes associated with Pleistocene sea level fluctuations on the East China Sea continental shelf may also have strongly influenced historical population demography and genetic diversity of marine organisms. Here, partial sequences of the mitochondrial Cytochrome c oxidase subunit I (COI) gene and seven microsatellite loci were used to estimate population genetic structure and demographic history of seven samples from Northern China coast and one sample from North Korea coast. Despite high levels of genetic diversity within samples, there was no genetic differentiation among samples from Northern China coast and low but significant genetic differentiation between some of the Chinese samples and the North Korean sample. A late Pleistocene population expansion, probably after the Last Glacial Maximum, was also demonstrated for A. pectinata samples. No recent genetic bottleneck was detected in any of the eight samples. We concluded that both historical recolonization (through population range expansion and demographic expansion in the late Pleistocene) and current gene flow (through larval dispersal) were responsible for the weak level of genetic structure detected in A. pectinata.

  12. f

    Table_5_Genetic variation of endangered Jankowski’s Bunting (Emberiza...

    • frontiersin.figshare.com
    docx
    Updated Jun 7, 2023
    + more versions
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    Long Huang; Guochen Feng; Dan Li; Weiping Shang; Lishi Zhang; Rongfei Yan; Yunlei Jiang; Shi Li (2023). Table_5_Genetic variation of endangered Jankowski’s Bunting (Emberiza jankowskii): High connectivity and a moderate history of demographic decline.DOCX [Dataset]. http://doi.org/10.3389/fevo.2022.996617.s012
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    Frontiers
    Authors
    Long Huang; Guochen Feng; Dan Li; Weiping Shang; Lishi Zhang; Rongfei Yan; Yunlei Jiang; Shi Li
    License

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

    Description

    IntroductionContinued discovery of “mismatch” patterns between population size and genetic diversity, involving wild species such as insects, amphibians, birds, mammals, and others, has raised issues about how population history, especially recent dynamics under human disturbance, affects currently standing genetic variation. Previous studies have revealed high genetic diversity in endangered Jankowski’s Bunting. However, it is unclear how the demographic history and recent habitat changes shape the genetic variation of Jankowski’s Bunting.MethodsTo explore the formation and maintenance of high genetic diversity in endangered Jankowski’s Bunting, we used a mitochondrial control region (partial mtDNA CR) and 15 nuclear microsatellite markers to explore the recent demographic history of Jankowski’s Bunting, and we compared the historical and contemporary gene flows between populations to reveal the impact of habitat change on population connectivity. Specifically, we aimed to test the following hypotheses: (1) Jankowski’s Bunting has a large historical Ne and a moderate demographic history; and (2) recent habitat change might have no significant impact on the species’ population connectivity.ResultsThe results suggested that large historical effective population size, as well as severe but slow population decline, may partially explain the high observable genetic diversity. Comparison of historical (over the past 4Ne generations) and contemporary (1–3 generations) gene flow indicated that the connectivity between five local populations was only marginally affected by landscape changes.DiscussionOur results suggest that high population connectivity and a moderate history of demographic decline are powerful explanations for the rich genetic variation in Jankowski’s Bunting. Although there is no evidence that the genetic health of Jankowski’s Bunting is threatened, the time-lag effects on the genetic response to recent environmental changes is a reminder to be cautious about the current genetic characteristics of this species. Where possible, factors influencing genetic variation should be integrated into a systematic framework for conducting robust population health assessments. Given the small contemporary population size, inbreeding, and ecological specialization, we recommend that habitat protection be maintained to maximize the genetic diversity and population connectivity of Jankowski’s Bunting.

  13. d

    Data from: Temporal variation in genetic diversity and effective population...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Jun 12, 2025
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    Nasr H. Gomaa; Alicia Montesinos-Navarro; Carlos Alonso-Blanco; F. Xavier Picó (2025). Temporal variation in genetic diversity and effective population size of Mediterranean and subalpine Arabidopsis thaliana populations [Dataset]. http://doi.org/10.5061/dryad.fv348
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    Dataset updated
    Jun 12, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Nasr H. Gomaa; Alicia Montesinos-Navarro; Carlos Alonso-Blanco; F. Xavier Picó
    Time period covered
    Jan 1, 2011
    Description

    Currently there exists a limited knowledge on the extent of temporal variation in population genetic parameters of natural populations. Here we study the extent of temporal variation in population genetics by genotyping 151 genome-wide SNP markers polymorphic in 466 individuals collected from nine populations of the annual plant Arabidopsis thaliana during four years. Populations are located along an altitudinal climatic gradient from Mediterranean to subalpine environments in NE Spain, which has been shown to influence key demographic attributes and life-cycle adaptations. Genetically, A. thaliana populations were more variable across space than over time. Common multilocus genotypes were detected several years in the same population, whereas low-frequency multilocus genotypes appeared only one year. High-elevation populations were genetically poorer and more variable over time than low-elevation populations, which might be caused by a higher overall demographic instability at higher a...

  14. d

    Genome-wide diversity and demographic dynamics of Cameroon goats and their...

    • datadryad.org
    • plos.figshare.com
    • +1more
    zip
    Updated Apr 25, 2019
    + more versions
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    Getinet M. Tarekegn; Patrick Wouobeng; Kouam S. Jaures; Raphael Mrode; Zewdu Edea; Bin Liu; Wenguang Zhang; Okeyo A. Mwai; Tadelle Dessie; Kassahun Tesfaye; Erling Strandberg; Britt Berglund; Mutai Mutai; Sarah Osama; Asaminew T. Wolde; Josephine Birungi; Appolinaire Djikeng; Félix Meutchieye (2019). Genome-wide diversity and demographic dynamics of Cameroon goats and their divergence from east African, north African, and Asian conspecifics [Dataset]. http://doi.org/10.5061/dryad.mc40jt6
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    zipAvailable download formats
    Dataset updated
    Apr 25, 2019
    Dataset provided by
    Dryad
    Authors
    Getinet M. Tarekegn; Patrick Wouobeng; Kouam S. Jaures; Raphael Mrode; Zewdu Edea; Bin Liu; Wenguang Zhang; Okeyo A. Mwai; Tadelle Dessie; Kassahun Tesfaye; Erling Strandberg; Britt Berglund; Mutai Mutai; Sarah Osama; Asaminew T. Wolde; Josephine Birungi; Appolinaire Djikeng; Félix Meutchieye
    Time period covered
    2019
    Area covered
    China, Cameroon, Iran, Ethiopia, Egypt, Morocco
    Description

    REVISED_ dataThe attached file is in ped format consists of 43421 markers of 848 animals after QC mentioned in the paper.REVISED_ dataMap file of the 43421 markers mentioned in the ped file.BioPed file of one population which consists of 44230 markers from 31 animals.BioMap file the 44230 markers ped file.

  15. n

    Data from: Noninvasive physiological markers demonstrate link between...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Sep 13, 2018
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    Jessica M. D. Lea; Susan L. Walker; Graham I. H. Kerley; John Jackson; Shelby C. Matevich; Susanne Shultz (2018). Noninvasive physiological markers demonstrate link between habitat quality, adult sex ratio and poor population growth rate in a vulnerable species, the Cape mountain zebra [Dataset]. http://doi.org/10.5061/dryad.d264r
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    zipAvailable download formats
    Dataset updated
    Sep 13, 2018
    Dataset provided by
    University of Manchester
    Nelson Mandela University
    Access to Seeds Foundation Amsterdam The Netherlands
    University of Sheffield
    Authors
    Jessica M. D. Lea; Susan L. Walker; Graham I. H. Kerley; John Jackson; Shelby C. Matevich; Susanne Shultz
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    South Africa, Cape Floristic Region
    Description

    Effective conservation and species management requires an understanding of the causes of poor population growth. Conservation physiology uses biomarkers to identify factors that contribute to low individual fitness and population declines. Building on this, macrophysiology can use the same markers to assess how individual physiology varies with different ecological or demographic factors over large temporal and spatial scales. Here, we use a macrophysiological approach to identify the ecological and demographic correlates of poor population growth rates in the Cape mountain zebra metapopulation. We use two non-invasive biomarkers: faecal glucocorticoids as a measure of chronic stress, and faecal androgens as an indicator of male physiological status. We found that faecal glucocorticoid concentrations were highest in the spring prior to summer rainfall, and were elevated in individuals from populations associated with low quality habitat (lower grass abundance). In addition, faecal androgen concentrations were higher in populations with a high proportion of non-breeding stallions (where male:female adult sex ratios exceed 2:1) suggesting sex ratio imbalances may intensify male competition. Finally, population growth rate was negatively associated with faecal glucocorticoid concentrations and female fecundity was negatively associated with faecal androgens, indicating a relationship between hormone profiles and fitness. Together, our results provide cross population evidence for how poor population growth rates in Cape mountain zebra can be linked to individual physiological biomarkers. More broadly, we advocate physiological biomarkers as indicators of population viability, and as a way to evaluate the impact of variable ecological and demographic factors. In addition, conservation physiology can be used to assess the efficacy of management interventions for this subspecies, and this approach could inform models of species’ responses to future environmental change.

  16. Data from: Challenges in analysis and interpretation of microsatellite data...

    • zenodo.org
    • data.niaid.nih.gov
    • +2more
    txt, zip
    Updated May 29, 2022
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    Alexander I. Putman; Ignazio Carbone; Alexander I. Putman; Ignazio Carbone (2022). Data from: Challenges in analysis and interpretation of microsatellite data for population genetic studies [Dataset]. http://doi.org/10.5061/dryad.j6567
    Explore at:
    txt, zipAvailable download formats
    Dataset updated
    May 29, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Alexander I. Putman; Ignazio Carbone; Alexander I. Putman; Ignazio Carbone
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (FST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

  17. s

    Visualisation of sequence and demographic data to assist HIV surveillance in...

    • eprints.soton.ac.uk
    Updated Jan 5, 2024
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    Dabis, François; Newell, Marie-Louise; Pillay, Deenan (2024). Visualisation of sequence and demographic data to assist HIV surveillance in Northern KwaZulu-Natal: extending the TasP/iSense dashboard to include markers of HIV drug resistance mutations [Dataset]. http://doi.org/10.23664/ahri.tasp.dataeverywhere.dashboard.2016.v1
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    Dataset updated
    Jan 5, 2024
    Dataset provided by
    Africa Health Research Institute
    Authors
    Dabis, François; Newell, Marie-Louise; Pillay, Deenan
    Area covered
    KwaZulu-Natal
    Description

    This proposal aims to extend an existing collaboration between AHRI and UCL. As part of the iSense project, teams from AHRI and UCL have successfully developed a dashboard that integrates information from mobile computers used for TasP field visits with data from the clinics to display spatial coverage of homestead visits, highlighting those that require follow-up visits to ensure linkage to care. The dashboard provides a broad snapshot of the state of the study, spatially aggregating geographical zones in order to preserve the privacy of trial participants. The aim of this proposal is to extend this framework to visualise presence and prevalence of drug resistance mutations (DRMs) within the study area. A higher prevalence of DRMs than expected may be linked to several factors, e.g. poor drug adherence, and thus of value to clinicians and healthcare workers in terms of focusing efforts and resource allocation.

  18. Data from: scCTS: identifying the cell type-specific marker genes from...

    • zenodo.org
    bin, zip
    Updated Sep 27, 2024
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    Luxiao Chen; Luxiao Chen; Guo Zhenxing; Guo Zhenxing; Tao Deng; Tao Deng; Hao Wu; Hao Wu (2024). scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq [Dataset]. http://doi.org/10.5281/zenodo.13850742
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    zip, binAvailable download formats
    Dataset updated
    Sep 27, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Luxiao Chen; Luxiao Chen; Guo Zhenxing; Guo Zhenxing; Tao Deng; Tao Deng; Hao Wu; Hao Wu
    License

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

    Description

    Single cell RNA-sequencing (scRNA-seq) provides gene expression profiles of individual cells from complex samples, facilitating the detection of cell type-specific marker genes. In scRNA-seq experiments with multiple donors, the population level variation brings an extra layer of complexity in cell type-specific gene detection, for example, they may not appear in all donors. Motivated by this observation, we develop a statistical model named scCTS to identify cell type-specific genes from population-level scRNA-seq data. Extensive data analyses demonstrate that the proposed method identifies more biologically meaningful cell type-specific genes compared to traditional methods.

  19. Fiducial Markers Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Fiducial Markers Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-fiducial-markers-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Fiducial Markers Market Outlook



    The global fiducial markers market is poised to experience significant growth, with the market size estimated to reach USD 140 million by 2023 and projected to expand to USD 300 million by 2032, reflecting a robust compound annual growth rate (CAGR) of 8.5% throughout the forecast period. The growth of the fiducial markers market is primarily driven by the increasing adoption of advanced imaging techniques in medical procedures and the rising prevalence of cancer, necessitating precise radiotherapy and image-guided surgeries. As healthcare systems worldwide prioritize precision in treatment modalities, the demand for fiducial markers is anticipated to witness a steady rise.



    One of the primary growth drivers in the fiducial markers market is the escalating incidence of cancer globally. With cancer being one of the leading causes of mortality, there is an urgent need for accurate and effective diagnostic and therapeutic solutions. Fiducial markers play a crucial role in enhancing the precision of radiotherapy and image-guided surgeries, ensuring targeted treatment and minimizing damage to surrounding healthy tissues. This precision is particularly vital in treating cancers located near critical organs where precision is paramount. Additionally, advancements in imaging technologies such as MRI, CT, and PET scans have further bolstered the demand for fiducial markers, as these markers facilitate enhanced visibility and accuracy in imaging.



    The increasing geriatric population is another significant factor contributing to market growth. As the global population ages, there is a corresponding rise in the incidence of age-related diseases, including various types of cancer. This demographic shift is anticipated to fuel the demand for fiducial markers, as older patients often require more precise and targeted therapeutic interventions. Furthermore, the growing preference for minimally invasive procedures is also driving the adoption of fiducial markers. Minimally invasive techniques, which rely heavily on accurate imaging, have become the standard of care in many surgical and therapeutic settings, further stimulating market expansion.



    The fiducial markers market is also benefiting from increased healthcare spending and technological advancements. Governments and private sectors around the world are investing heavily in healthcare infrastructure, technology, and research to improve patient outcomes. This investment is fostering the development of advanced fiducial markers with enhanced properties such as biocompatibility and stability. The integration of fiducial markers with other advanced medical technologies, such as robotic surgery and artificial intelligence, is expected to create new opportunities for market growth. Additionally, the growing awareness among healthcare professionals and patients regarding the benefits of precise treatment planning is further propelling the market forward.



    Medical Skin Markers are increasingly being recognized as essential tools in the field of precision medicine. These markers are specifically designed for use on the skin, providing clear and accurate reference points for various medical procedures. In the context of radiotherapy and image-guided surgeries, Medical Skin Markers help in delineating treatment areas, ensuring that radiation or surgical interventions are precisely targeted. Their application is particularly beneficial in cases where external markers are preferred over implanted ones, offering a non-invasive option for patient care. The development of advanced Medical Skin Markers with improved visibility and durability is further enhancing their utility in clinical settings.



    Regionally, North America holds a substantial share of the fiducial markers market, driven by the presence of advanced healthcare infrastructure, a high prevalence of cancer, and significant investment in research and development. Europe also represents a significant market, with countries like Germany, France, and the UK leading in the adoption of advanced medical technologies. The Asia Pacific region is expected to witness the fastest growth, attributed to the rapidly improving healthcare infrastructure, increasing healthcare expenditure, and a rising incidence of cancer. The Middle East & Africa, along with Latin America, are also anticipated to contribute to market expansion, albeit at a slower pace, due to developing healthcare systems and increasing awareness.



    Product Type Analysis



    Fidu

  20. d

    Data from: Y-chromosome markers for the red fox

    • search.dataone.org
    • data.niaid.nih.gov
    • +2more
    Updated Jun 10, 2025
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    Halie M. Rando; Jeremy T. Stutchman; Estelle R. Bastounes; Jennifer L. Johnson; Carlos A. Driscoll; Christina S. Barr; Lyudmila N. Trut; Benjamin N. Sacks; Anna V. Kukekova (2025). Y-chromosome markers for the red fox [Dataset]. http://doi.org/10.5061/dryad.fq7dj
    Explore at:
    Dataset updated
    Jun 10, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Halie M. Rando; Jeremy T. Stutchman; Estelle R. Bastounes; Jennifer L. Johnson; Carlos A. Driscoll; Christina S. Barr; Lyudmila N. Trut; Benjamin N. Sacks; Anna V. Kukekova
    Time period covered
    Jul 14, 2020
    Description

    The de novo assembly of the red fox (Vulpes vulpes) genome has facilitated the development of genomic tools for the species. Efforts to identify the population history of red foxes in North America have previously been limited by a lack of information about the red fox Y-chromosome sequence. However, a megabase of red fox Y-chromosome sequence was recently identified over 2 scaffolds in the reference genome. Here, these scaffolds were scanned for repeated motifs, revealing 194 likely microsatellites. Twenty-three of these loci were selected for primer development and, after testing, produced a panel of 11 novel markers that were analyzed alongside 2 markers previously developed for the red fox from dog Y-chromosome sequence. The markers were genotyped in 76 male red foxes from 4 populations: 7 foxes from Newfoundland (eastern Canada), 12 from Maryland (eastern United States), and 9 from the island of Great Britain, as well as 48 foxes of known North American origin maintained on an expe...

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National Institute of Standards and Technology (2023). U.S. population data for human identification markers [Dataset]. https://catalog.data.gov/dataset/u-s-population-data-for-human-identification-markers
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U.S. population data for human identification markers

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4 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 7, 2023
Dataset provided by
National Institute of Standards and Technologyhttp://www.nist.gov/
Area covered
United States
Description

The primary data consist of allele or haplotype frequencies for N=1036 anonymized U.S. population samples. Additional files are supplements to the associated publications. Any changes to spreadsheets are listed in the "Change Log" tab within each spreadsheet. DOI numbers for associated publications are listed below, under "References".

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