Geolocation prediction from STR genotyping: a pilot study in five geographically distinct global populations Article Swipe
Mansi Arora
,
Hirak Ranjan Dash
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1080/03014460.2023.2217382
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1080/03014460.2023.2217382
Three different prediction models have been proposed for genotype to geolocation prediction, i.e. (i) use of unique genotypes of a population, (ii) use of the most frequent genotype, and (iii) a combinatorial approach of unique and most frequent genotypes. These models could aid the investigating agencies in cases where no reference sample is available for comparison of the profile.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/03014460.2023.2217382
- https://www.tandfonline.com/doi/pdf/10.1080/03014460.2023.2217382?needAccess=true&role=button
- OA Status
- gold
- Cited By
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- References
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https://doi.org/10.1080/03014460.2023.2217382Digital Object Identifier
- Title
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Geolocation prediction from STR genotyping: a pilot study in five geographically distinct global populationsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
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2023Year of publication
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2023-01-02Full publication date if available
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Mansi Arora, Hirak Ranjan DashList of authors in order
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https://doi.org/10.1080/03014460.2023.2217382Publisher landing page
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https://www.tandfonline.com/doi/pdf/10.1080/03014460.2023.2217382?needAccess=true&role=buttonDirect link to full text PDF
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goldOpen access status per OpenAlex
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https://www.tandfonline.com/doi/pdf/10.1080/03014460.2023.2217382?needAccess=true&role=buttonDirect OA link when available
- Concepts
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Geolocation, Genotyping, Geography, Demography, Biology, Evolutionary biology, Statistics, Genetics, Computer science, Genotype, Mathematics, World Wide Web, Sociology, GeneTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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32Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3048751432, https://openalex.org/W2107519321, https://openalex.org/W2967542552, https://openalex.org/W3132013914, https://openalex.org/W2155275250, https://openalex.org/W2996750965, https://openalex.org/W2801300241, https://openalex.org/W2168220519, https://openalex.org/W2166924875, https://openalex.org/W2170059665, https://openalex.org/W141295380, https://openalex.org/W2088583835, https://openalex.org/W3124098938, https://openalex.org/W3216011169, https://openalex.org/W2302845675, https://openalex.org/W3124019253, https://openalex.org/W2123665956, https://openalex.org/W2589114557, https://openalex.org/W2596362587, https://openalex.org/W3003167748, https://openalex.org/W2754106524, https://openalex.org/W2971497029, https://openalex.org/W1991243237, https://openalex.org/W2101207464, https://openalex.org/W2149588035, https://openalex.org/W2158580306, https://openalex.org/W2036317497, https://openalex.org/W2981530141, https://openalex.org/W2061301918, https://openalex.org/W2018096099, https://openalex.org/W2588492423, https://openalex.org/W1971522751 |
| referenced_works_count | 32 |
| abstract_inverted_index.a | 19, 30 |
| abstract_inverted_index.in | 46 |
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| abstract_inverted_index.no | 49 |
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| abstract_inverted_index.(i) | 13 |
| abstract_inverted_index.aid | 42 |
| abstract_inverted_index.and | 28, 35 |
| abstract_inverted_index.for | 7, 54 |
| abstract_inverted_index.the | 24, 43, 57 |
| abstract_inverted_index.use | 14, 22 |
| abstract_inverted_index.(ii) | 21 |
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| abstract_inverted_index.have | 4 |
| abstract_inverted_index.i.e. | 12 |
| abstract_inverted_index.most | 25, 36 |
| abstract_inverted_index.(iii) | 29 |
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| abstract_inverted_index.Three | 0 |
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| abstract_inverted_index.frequent | 26, 37 |
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| abstract_inverted_index.comparison | 55 |
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| abstract_inverted_index.population, | 20 |
| abstract_inverted_index.prediction, | 11 |
| abstract_inverted_index.combinatorial | 31 |
| abstract_inverted_index.investigating | 44 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5070492520 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I1331084196 |
| citation_normalized_percentile.value | 0.76357876 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |