31 to 40 of 892 Results
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Tab-Delimited
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
Apr 11, 2026 - Rīga Stradiņš University
Irmejs, Arvīds; Loža, Pēteris; Maksimenko, Jeļena; Daneberga, Zanda; Liepiņa, Elza Elizabete; Čerņeikina, Anneta, 2026, "Development of Genetic Testing Strategies for Hereditary Breast and Ovarian Cancer Risk Prediction by Analysis of Spectrum of Predisposing Mutations and Their Phenotypic Manifestations: Clinical Data", https://doi.org/10.48510/FK2/AJIIVR, UNF:6:lYl2b0nqg1ects0ji1GdSg== [fileUNF]
The clinical data of retrospective cohort were collected to calculate Manchester score and CanRisk tool value for all breast and ovarian cancer cases. The NGS targeted panel including 9 genes was performed for samples with previously negative genetic testing results and available biological material. Pathogenicity of genetic variants were classifie...This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
Apr 11, 2026 - Rīga Stradiņš University
Irmejs, Arvīds; Loža, Pēteris; Maksimenko, Jeļena; Daneberga, Zanda; Liepiņa, Elza Elizabete; Čerņeikina, Anneta, 2026, "Development of Genetic Testing Strategies for Hereditary Breast and Ovarian Cancer Risk Prediction by Analysis of Spectrum of Predisposing Mutations and Their Phenotypic Manifestations: Genetic Data", https://doi.org/10.48510/FK2/B4V921, UNF:6:gYwYsyBKvsICe/EutRp+rA== [fileUNF]
The NGS targeted panel including 9 genes was performed for samples with previously negative genetic testing results and available biological material. Pathogenicity of genetic variants were classified using a standardized framework developed by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology...This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
Apr 9, 2026 - Social Sciences
Mirke, Evija, 2026, "Survey Data on Latvian K-12 Teachers' Readiness for Generative Artificial Intelligence Adoption", https://doi.org/10.71782/DATA/YRM6OS, DataverseLV, V1
This dataset contains quantitative data collected through a cross-sectional survey of K-12 teachers from all regions of Latvia in 2024–2025. The survey measured teachers' readiness to adopt generative artificial intelligence tools using an adapted version of the Technology Readiness Index (TRI 2.0) framework, which was adapted specifically for gene... |
Apr 9, 2026 -
Survey Data on Latvian K-12 Teachers' Readiness for Generative Artificial Intelligence Adoption
Comma Separated Values - 112.1 KB -
MD5: 87a8cd32d197ffbdf63b7137187c9170
DATA |
Apr 9, 2026 -
Survey Data on Latvian K-12 Teachers' Readiness for Generative Artificial Intelligence Adoption
Plain Text - 14.3 KB -
MD5: 098f2bb045bbf84d81b593416fbefdb6
README_LV |
Adobe PDF
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
Adobe PDF
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
Adobe PDF
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
