Although artificial neural networks are powerful classifiers, their internal structures are hard to interpret. In the life sciences, extensive knowledge of cell biology provides an opportunity to ...

Your modeling efforts are going to be fruitless. This catch is not specific to linear regression. It applies to any machine learning model in any domain — if the features available aren’t ...

Most importantly, it helps to pick a machine learning model that will work better with sparse data. Linear regression and tree-based models are both at risk for needing more memory space and taking ...

uses machine learning to rapidly predict 3D protein structures that are so accurate they are indistinguishable from those experimentally derived by scientists. This open-source model has been used ...

finesse that so that you start capturing what is happening in structure,’ we are able to get the model to capture the hypervariable regions in a transfer learning setting,” Singh said.

which are highly advanced physics-based machine learning models. PepFlow can also model peptide structures that take on unusual formations, such as the ring-like structure that results from a ...