Data from: Determining the subcellular location of new proteins from microscope images using local features

Here, we frame a more challenging and useful problem where previously unseen proteins are to be classified. Results: Using CD-tagging, we generated two new image datasets for evaluation of this problem, which contain several different proteins for each location class.

Evaluation of previous methods on these new datasets showed that it is much harder to train a classifier that generalizes across different proteins than one that simply recognizes a protein it was trained on. We therefore developed and evaluated additional approaches, incorporating novel modifications of local features techniques. These extended the notion of local features to exploit both the protein image and any reference markers that were imaged in parallel.