Sentence examples for built a linear model from inspiring English sources
We first built a linear model predicting ChIP-seq reads from mappability alone, and determined how much of the ChIP-seq signal was explained.
We first built a linear model using SSOG counts observed in all insects relative to their estimated divergence time to MRCA excluding ants and A pi. mellifera.
Based on our experiences we have built a linear model for the length of time that contributors are likely to donate to a crowd-sourced citizen science project.
To examine the effect of DNA methylation on recombination while controlling for other factors, we built a linear model where recombination rates were response variables, and several sequence features (G+C content, number of CpGs, proportion of repeats) and sperm DNA methylation level were predictor variables.
To assess the relationship between age at draw and multiple expression levels, we employed the LASSO algorithm of Tibshirani (Tibshirani, 1996; Efron et al., 2004) to build a linear model of age at draw as a function of multiple expression levels.
IED onsets were used to build a linear model of the effects of interest by convolution with a canonical hemodynamic response function (HRF, event-related design) and its temporal derivative to account for possible variations in the blood oxygen level-dependent (BOLD) response delay.
For example, Narlikar et al. built a linear regression model to identify active enhancers in heart based on 727 sequence features including 721 TF binding related genetic features [65].
We built a linear regression model and calculated the coefficient of determination R 2 to measure the strength of association between all possible permutations of variables.
Thus, we manually built a linear regression model in SPSS (Statistical Package for Social Sciences) V.16 and SAS (Statistical Analysis System) V.9.2.
To calculate the loss of income in families with ASD or OD children, we built a linear regression model using a sample of families with TD children to obtain the predicted household income in the ASD and OD groups based on parental socioeconomic status and demographics.
