Michael Seiler

Michael Seiler has been instrumental in computational analysis of spliceosome inhibitors E7107 and pladienolide B, characterizing their genome-wide effects on RNA splicing and identifying biomarkers of sensitivity in cancer cells. His computational approaches mapped the intron retention and exon skipping patterns induced by spliceosome inhibitors across hundreds of cancer cell lines. He contributed to identifying SF3B1 mutation status as a predictive biomarker for spliceosome modulator response. His bioinformatics work has been essential for clinical development of splicing-targeted cancer therapeutics.