BioinformaticsIEEE International Conference on Bioinformatics and Biomedicine (BIBM)Peer-reviewed
Multiple Confounders Correction with Regularized Linear Mixed Effect Models, with Application in Biological Processes
The paper evaluates regularized linear mixed effect models for correcting multiple confounders in biological data, finding that sequence-based correction performs best when confounders contribute equally.
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