PANDA: Protein Function Prediction Using Domain Architecture and Affinity Propagation
Document Type
Article
Publication Date
12-1-2018
School
Computing Sciences and Computer Engineering
Abstract
© 2018 The Author(s). We developed PANDA (Propagation of Affinity and Domain Architecture) to predict protein functions in the format of Gene Ontology (GO) terms. PANDA at first executes profile-profile alignment algorithm to search against PfamA, KOG, COG, and SwissProt databases, and then launches PSI-BLAST against UniProt for homologue search. PANDA integrates a domain architecture inference algorithm based on the Bayesian statistics that calculates the probability of having a GO term. All the candidate GO terms are pooled and filtered based on Z-score. After that, the remaining GO terms are clustered using an affinity propagation algorithm based on the GO directed acyclic graph, followed by a second round of filtering on the clusters of GO terms. We benchmarked the performance of all the baseline predictors PANDA integrates and also for every pooling and filtering step of PANDA. It can be found that PANDA achieves better performances in terms of area under the curve for precision and recall compared to the baseline predictors. PANDA can be accessed from http://dna.cs.miami.edu/PANDA/.
Publication Title
Scientific Reports
Volume
8
Issue
1
First Page
1
Last Page
10
Recommended Citation
Wang, Z.,
Zhao, C.,
Wang, Y.,
Sun, Z.,
Wang, N.
(2018). PANDA: Protein Function Prediction Using Domain Architecture and Affinity Propagation. Scientific Reports, 8(1), 1-10.
Available at: https://aquila.usm.edu/fac_pubs/18320