Is the outlier detection appropriate for protein protein interaction data?

Ayyıldız Demirci, Ezgi
Purutçuoğlu Gazi, Vilda


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Motivation Lately. deep learning-based models for drug-target interaction (DTI) prediction have yielded highly promising results. However. the majority of proposed deep learning models developed so far require large-scale training data. For many proteins. there is very little bioactivity data recorded in the databases or none at all; therefore. no prediction models are available for these. For example. in ChEMBL_29. only 8% of proteins have more than 1.000 bioactive compounds. while 56% of the proteins have...
Is it necessary to apply the outlier detection for protein-protein interaction data?
Ayyıldız, Ezgi; Purutçuoğlu Gazi, Vilda (2018-01-01)
Objective: Outlier detection is a crucial problem in many fields. Although there are too many outlier detection methods in the literature, only a few methods suitable for dependent, sparse and high dimensional data structure. In this study, we perform various univariate and multivariate outlier detection methods as a pre-processing step before modeling the protein-protein interaction networks in order to investigate whether the outlier detection can improve the accuracy of the model. Material and Methods: W...
Citation Formats
E. Ayyıldız Demirci and V. Purutçuoğlu Gazi, “Is the outlier detection appropriate for protein protein interaction data?,” 2018, Accessed: 00, 2021. [Online]. Available: