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In this article, we have demonstrated a methodology which, by modelling the analysis and decision process of an experienced scientist, can substantially speed up validation of a large scale phosphoproteomics dataset by processing the data with 80 95% confidence in the positive validations and with a high sensitivity.
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And these effects are well modeled in the analysis.
Similar to the analytical model, the analysis was performed in two steps.
To check the accuracy of the model, the analysis of variance (ANOVA) method has been used.
In this model, the analysis dictionary multiplying the signal can lead to a sparse outcome.
According to this model, the analysis of the bioprocess stability is presented.
We term this model the analysis model.
For the validation of the described model, the analysis of residues was also assessed.
Both authors contributed equally to the formulation of the model, the analysis, and the writing of the manuscript.
In the final models, the analysis of the jackknife residuals showed that assumptions of the linear regression had been respected.
In the fourth model, the final model of the analysis, the variable "psychosocial symptoms" was added.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com