https://www.sciencedaily.com/releases/2023/06/230621164746.htm

A group of scientists at the Wyss Institute for Biologically Inspired Engineering at Harvard University and MIT has now filled that unmet need by building a new, comprehensive AutoML platform designed for biologists with little to no ML experience. Their platform, called BioAutoMATED, can use sequences of nucleic acids, peptides, or glycans as input data, and its performance is comparable to other AutoML platforms while requiring minimal user input. The platform is described in a new paper published in Cell Systems and is available to download from GitHub.

"Our tool is for folks who don't have the ability to build their own custom ML models, who find themselves asking questions like, 'I have this cool data set, will ML even work for it? How do I get it into an ML model? The complexity of ML is what's stopping me from going further with this data set, so how do I overcome that?'," said co-first author Jackie Valeri, a graduate student in the lab of Wyss Core Faculty member Jim Collins, Ph.D. "We wanted to make it easy for biologists and experts in other domains to use the power of ML and AutoML to answer fundamental questions and help uncover biology that means something."