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SNP-based prediction of schizophrenia using machine learning
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| Published in: | Bioinformatics Advances : Journal of the International Society for Computational Biology |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1864030189350027268 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Bioinformatics Advances : Journal of the International Society for Computational Biology |
| description | |
| discipline_display | Natural Sciences |
| discipline_facet | Natural Sciences |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:18846 |
| institution | FRELIP |
| journal_source_facet | Bioinformatics Advances : Journal of the International Society for Computational Biology |
| publishDate | 2025 |
| publishDateSort | 2025 |
| record_format | rss_article |
| spellingShingle | SNP-based prediction of schizophrenia using machine learning Biology Natural Sciences — Life Sciences Natural Sciences |
| sub_discipline_display | Natural Sciences — Life Sciences |
| sub_discipline_facet | Natural Sciences — Life Sciences |
| subject_display | Biology Natural Sciences — Life Sciences Natural Sciences Biology Natural Sciences — Life Sciences Natural Sciences |
| subject_facet | Biology Natural Sciences — Life Sciences Natural Sciences |
| title | SNP-based prediction of schizophrenia using machine learning |
| title_auth | SNP-based prediction of schizophrenia using machine learning |
| title_full | SNP-based prediction of schizophrenia using machine learning |
| title_fullStr | SNP-based prediction of schizophrenia using machine learning |
| title_full_unstemmed | SNP-based prediction of schizophrenia using machine learning |
| title_short | SNP-based prediction of schizophrenia using machine learning |
| title_sort | snp-based prediction of schizophrenia using machine learning |
| topic | Biology Natural Sciences — Life Sciences Natural Sciences |
| url | https://academic.oup.com/bioinformaticsadvances/article/doi/10.1093/bioadv/vbaf219/8275734?rss=1 |