A new “In Focus” piece by Mike Keiser and Kangway Chuang makes the cover of ACS Chemical Biology

Keiser Chuang ACS Chemical Biology Machine Learning AI UCSFIn a new “In Focus” article in ACS Chemical Biology, IND Assistant Professor In-Residence Mike Keiser and postdoc Kangway Chuang stress caution when applying machine learning to experimental research models. With new machine learning methods broadly accessible to the research community, Keiser and Chuang emphasize the continued importance of designing strong control experiments and argue that a “hypothesis-driven approach” to research design is “now more critical than ever”.

Read the full abstract and article here