Protein Function Prediction: DeepGOPlus Model for Improved Sequence-based Prediction

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Protein Function Prediction
Prediction of protein function refers to one of the major but important tasks of bioinformatics,
where a number of techniques are used for determining the range of biological problems, in
terms of role of protein in developing disease mechanisms, so that targeted drugs could find. It
includes sequence based features, protein structure, protein–protein interaction networks and
other bioinformatics tools used for analysing the composition of molecules and model of
biological system, by collecting genomic data. Predictions of protein structure helps in producing
automatically the predicted protein structures by using amino acid sequence. However, these
methods may consume a lot of time for predicting the protein functions, therefore, a new model
is developed in this article by Maxat Kulmanove and Robert Hoehndorf as DeepGOPlus, for
improving the function prediction from sequence. But before developing this model, a proper
study is conducted to determine the factors that arise limitations in performance of DeepGO
model. It has been identified by the researchers that DeepGO model only predicts protein