Hierarchical deep learning for predicting go annotations by integrating protein knowledge

HIGHLIGHTS

• who: from the (UNIVERSITY) have published the Article: Hierarchical deep learning for predicting GO annotations by integrating protein knowledge, in the Journal: (JOURNAL)

SUMMARY

It can be seen here that, in most cases, similar patterns were found for each sub-ontologies, even when the model inputs were different. Particularly, 64 was the optimal value for the largest sub-ontology (BP), and 16 was the best batch size for the smallest one (CC). In the case of MF, the difference in model Fmax achieved using batch sizes of 16 and 64 is around 0 . . .

 



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