est from human unigene database Search Results


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Incyte corporation unigem v human gem 1 microarrays
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ATCC 16s 23s ribosomal rna intergenic spacer
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Genome Systems Inc human unigem v microarray
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Incyte corporation cdna microarray
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Unigene human unigene cluster hs
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91
Thermo Fisher gene exp fnip1 hs00382846 m1
Multifactorial genetic model for overweight and obesity risk. A Multifactorial model to predict body mass index (BMI). Estimated parameters and 95% CI, plus p -values of variables in the multifactorial model. The linear regression model included the rs2291007 SNP (in additive form), three gene expression variables ( FNIP2 , <t>FNIP1</t> , and FLCN ), plus sex, age, and the interaction between FNIP2 gene expression and rs2291007. B Bootstrap validation of the multifactorial model. Multifactorial model was validated through bootstrap validation, using 2000 bootstrap samples, which correction by optimism (MSE, Mean Square Error). C Variable importance plot for the multifactorial model, using χ 2 – df (degrees of freedom) as metrics for the importance of each variable
Gene Exp Fnip1 Hs00382846 M1, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 91/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Multifactorial genetic model for overweight and obesity risk. A Multifactorial model to predict body mass index (BMI). Estimated parameters and 95% CI, plus p -values of variables in the multifactorial model. The linear regression model included the rs2291007 SNP (in additive form), three gene expression variables ( FNIP2 , FNIP1 , and FLCN ), plus sex, age, and the interaction between FNIP2 gene expression and rs2291007. B Bootstrap validation of the multifactorial model. Multifactorial model was validated through bootstrap validation, using 2000 bootstrap samples, which correction by optimism (MSE, Mean Square Error). C Variable importance plot for the multifactorial model, using χ 2 – df (degrees of freedom) as metrics for the importance of each variable

Journal: Genome Biology

Article Title: Folliculin-interacting protein FNIP2 impacts on overweight and obesity through a polymorphism in a conserved 3′ untranslated region

doi: 10.1186/s13059-022-02798-5

Figure Lengend Snippet: Multifactorial genetic model for overweight and obesity risk. A Multifactorial model to predict body mass index (BMI). Estimated parameters and 95% CI, plus p -values of variables in the multifactorial model. The linear regression model included the rs2291007 SNP (in additive form), three gene expression variables ( FNIP2 , FNIP1 , and FLCN ), plus sex, age, and the interaction between FNIP2 gene expression and rs2291007. B Bootstrap validation of the multifactorial model. Multifactorial model was validated through bootstrap validation, using 2000 bootstrap samples, which correction by optimism (MSE, Mean Square Error). C Variable importance plot for the multifactorial model, using χ 2 – df (degrees of freedom) as metrics for the importance of each variable

Article Snippet: RT-PCR reactions were performed as previously described [ ] using QuantStudio 12 K Flex Real-Time PCR System (Life Technologies Inc., Carlsbad, CA, USA), with specific Taqman probes: FNIP2 (Hs01574322_m1), FLCN (Hs00376065_m1), FNIP1 (Hs00382846_m1), GAPDH (Hs02786624_g1).

Techniques: Gene Expression, Biomarker Discovery