Michael G. Endres

This study evaluates deconvolution methods for gene expression data using an open innovation competition and finds that random forest regression outperforms other approaches in accuracy and reproducibility.

The paper demonstrates how open innovation competitions improve computational biology methods for antibody clustering, gene expression imputation, and CMap querying.