Classifying GABAergic interneurons with semi-supervised projected model-based clustering

Conclusions The applied semi-supervised clustering method can accurately discriminate among CB, HT, LB, and MA interneuron types while discovering potential subtypes, and is therefore useful for neuronal classification. The discovery of potential subtypes suggests that some of these types are more heterogeneous that previously thought. Finally, axonal variables seem to be more relevant than dendritic ones for distinguishing among the CB, HT, LB, and MA interneuron types.

Source: Artificial Intelligence in Medicine - January 8, 2015 Category: Bioinformatics Source Type: research