title: osFP: a web server for predicting the oligomeric states of fluorescent proteins.
abstract: BACKGROUND
  Currently, monomeric fluorescent proteins (FP) are ideal markers for protein tagging. The prediction of oligomeric states is helpful for enhancing live biomedical imaging. Computational prediction of FP oligomeric states can accelerate the effort of protein engineering efforts of creating monomeric FPs. To the best of our knowledge, this study represents the first computational model for predicting and analyzing FP oligomerization directly from the amino acid sequence.
  
  
  RESULTS
  After data curation, an exhaustive data set consisting of 397 non-redundant FP oligomeric states was compiled from the literature. Results from benchmarking of the protein descriptors revealed that the model built with amino acid composition descriptors was the top performing model with accuracy, sensitivity and specificity in excess of 80% and MCC greater than 0.6 for all three data subsets (e.g. training, tenfold cross-validation and external sets). The model provided insights on the important residues governing the oligomerization of FP. To maximize the benefit of the generated predictive model, it was implemented as a web server under the R programming environment.
  
  
  CONCLUSIONS
  osFP affords a user-friendly interface that can be used to predict the oligomeric state of FP using the protein sequence. The advantage of osFP is that it is platform-independent meaning that it can be accessed via a web browser on any operating system and device. osFP is freely accessible at http://codes.bio/osfp/ while the source code and data set is provided on GitHub at https://github.com/chaninn/osFP/.Graphical Abstract.
authors.affiliation: Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
authors.forename: Saw
authors.initials: S
authors.lastname: Simeon
authors.affiliation: Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
authors.forename: Watshara
authors.initials: W
authors.lastname: Shoombuatong
authors.affiliation: Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
authors.forename: Nuttapat
authors.initials: N
authors.lastname: Anuwongcharoen
authors.affiliation: Department of Community Medical Technology, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
authors.forename: Likit
authors.initials: L
authors.lastname: Preeyanon
authors.affiliation: Department of Community Medical Technology, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
authors.forename: Virapong
authors.initials: V
authors.lastname: Prachayasittikul
authors.affiliation: Department of Pharmaceutical Biosciences, Uppsala University, 751 24 Uppsala, Sweden.
authors.forename: Jarl E S
authors.initials: JE
authors.lastname: Wikberg
authors.affiliation: Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok, 10700 Thailand.
authors.forename: Chanin
authors.identifier: 0000-0003-1040-663X
authors.initials: C
authors.lastname: Nantasenamat
keywords: Data mining; FP; Fluorescent protein; GFP; Green fluorescent protein; Oligomeric state; Web server