How to deal with unbalanced class in biological datasets?
There can be two things for an imbalanced dataset:

. For eg, in a cancer detection dataset, the number of positive(cancer present) samples, will be quite less than the negative( cancer absent) samples. In this case, you should not apply sampling technqiues. You should rather focus on minimizing False Negatives , as cancer should not be missed while diagnosing a patient at the expense of a few false positives.

.Second case, for eg, The popular  Iris Datset where the classes should be balanced. But suppose you get an imbalanced version of the dataset, then you should apply sampling technqiues to the dataset. Because, the class proportion does not match the actual proportion , which was not the case in the Cancer Example.