Abstract：
: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/ .
journal_name
Sci Repjournal_title
Scientific reportsauthors
Wang Z,Zhao C,Wang Y,Sun Z,Wang Ndoi
10.1038/s41598-018-21849-1subject
Has Abstractpub_date
2018-02-22 00:00:00pages
3484issue
1issn
2045-2322pii
10.1038/s41598-018-21849-1journal_volume
8pub_type
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pub_type： 杂志文章
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