SEECER
SEquencing Error CorrEction for RNA sequencing data (SEECER) is a read error correction method designed for non-uniform sequencing data sets, in particular RNA-seq. It clusters reads and reconstructs profile HMMs to correct indel and substitution errors with high sensitivity.
Authors
Marcel H. Schulz, PhD
(he/him)
Professor for Computational Biology
I am a Computational Biologist by education. I develop computational
systems biology models and machine learning algorithms that further
the understanding of gene regulation. We work on groundbreaking computational methods
that enable novel approaches for personalized medicine applications in the
context of different human diseases. We live and breathe open-source development.