Hierarchical deep learning for predicting go annotations by integrating protein knowledge

HIGHLIGHTS

• who: Bioinformatics and colleagues from the Research Institute for Signals, Systems and Computational Intelligence (sinc(i)), FICH-UNL, CONICET, Ciudad Universitaria UNL, Santa Campus, Cambridge CB SD, UK have published the article: Hierarchical deep learning for predicting GO annotations by integrating protein knowledge, in the Journal: (JOURNAL)
• what: The authors propose DeeProtGO a novel deep-learning model for predicting GO annotations by integrating protein knowledge. The experiments reported higher prediction quality when more protein knowledge is integrated. The authors show how the combination of more than one type of protein information could improve the prediction . . .
  

   

  

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