We develop
machine learning
techniques to better understand chromatin
biology. These models and algorithms transform
high-dimensional functional genomics data
into interpretable patterns and lead to new biological insight.
2022-04-20: Michael is an invited panelist to present his talk "Acidbio and BED" at the panel "Testbeds and validation of standards", The GA4GH Connect meeting.
2022-04-13: Michael is an invited speaker to present his talk "Predicting transcription factor binding and the effects of viral integration" at a Computational Biology Seminar Series at the Garvan Institute of Medical Research in Sydney, Australia.