Predicted PPIs have been around a long time. However, there is a wave of new prediction methods that are attempting to capitalize on the successes of machine learning for proteins (including 3D structure prediction). For example:
We can use SPRAS to consider how pathway reconstruction interacts with these types of predicted networks. Does running on a larger, predicted yeast network give different/better pathways than experimental PPI? Does the existence of a predicted PPI network give us enough of a foothold to run pathway reconstruction on species where little to no experimental data exist?
Predicted PPIs have been around a long time. However, there is a wave of new prediction methods that are attempting to capitalize on the successes of machine learning for proteins (including 3D structure prediction). For example:
We can use SPRAS to consider how pathway reconstruction interacts with these types of predicted networks. Does running on a larger, predicted yeast network give different/better pathways than experimental PPI? Does the existence of a predicted PPI network give us enough of a foothold to run pathway reconstruction on species where little to no experimental data exist?