ArticleFEBS open bio2019
Development of a general logistic model for disease risk prediction using multiple SNPs.
Article in FEBS open bio, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- HOTTIP rs1859168 C > A polymorphism reduces neuroblastoma susceptibility in Chinese children.European journal of pediatrics · 2024Article
- Article
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3 authors.
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Abstract
Human diseases are usually linked to multiloci genetic alterations, including single-nucleotide polymorphisms (SNPs). Methods to use these SNPs for disease risk prediction (DRP) are of clinical interest. DRP algorithms explored by commercial companies to date have tended to be complex and led to controversial prediction results. Here, we present a general approach for establishing a logistic model-based DRP algorithm, in which multiple SNP risk factors from different publications are directly used. In particular, the coefficient β of each SNP is set as the natural logarithm of the reported odds ratio, and the constant coefficient β
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