Journal
BMC BIOINFORMATICS
Volume 19, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12859-018-2396-7
Keywords
-
Categories
Funding
- RIKEN, Center for Integrative Medical Sciences, Japan
- CREST, JST, Yokohama, Japan
Ask authors/readers for more resources
BackgroundMolecular Recognition Features (MoRFs) are short protein regions present in intrinsically disordered protein (IDPs) sequences. MoRFs interact with structured partner protein and upon interaction, they undergo a disorder-to-order transition to perform various biological functions. Analyses of MoRFs are important towards understanding their function.ResultsPerformance is reported using the MoRF dataset that has been previously used to compare the other existing MoRF predictors. The performance obtained in this study is equivalent to the benchmarked OPAL predictor, i.e., OPAL achieved AUC of 0.815, whereas the model in this study achieved AUC of 0.819 using TEST set.ConclusionAchieving comparable performance, the proposed method can be used as an alternative approach for MoRF prediction.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available