title: FUEL-mLoc: feature-unified prediction and explanation of multi-localization of cellular proteins in multiple organisms.
abstract: Although many web-servers for predicting protein subcellular localization have been developed, they often have the following drawbacks: (i) lack of interpretability or interpreting results with heterogenous information which may confuse users; (ii) ignoring multi-location proteins and (iii) only focusing on specific organism. To tackle these problems, we present an interpretable and efficient web-server, namely FUEL-mLoc, using eature- nified prediction and xplanation of m ulti- oc alization of cellular proteins in multiple organisms. Compared to conventional localization predictors, FUEL-mLoc has the following advantages: (i) using unified features (i.e. essential GO terms) to interpret why a prediction is made; (ii) being capable of predicting both single- and multi-location proteins and (iii) being able to handle proteins of multiple organisms, including Eukaryota, Homo sapiens, Viridiplantae, Gram-positive Bacteria, Gram-negative Bacteria and Virus . Experimental results demonstrate that FUEL-mLoc outperforms state-of-the-art subcellular-localization predictors.
  
  
  
  http://bioinfo.eie.polyu.edu.hk/FUEL-mLoc/.
  
  
  
  shibiao.wan@princeton.edu or enmwmak@polyu.edu.hk.
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Electrical Engineering, Princeton University, NJ, USA.
authors.forename: Shibiao
authors.initials: S
authors.lastname: Wan
authors.affiliation: Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China.
authors.forename: Man-Wai
authors.initials: MW
authors.lastname: Mak
authors.affiliation: Department of Electrical Engineering, Princeton University, NJ, USA.
authors.forename: Sun-Yuan
authors.initials: SY
authors.lastname: Kung
mesh_terms: D001419:Bacteria / Q000378:metabolism; D002451:Cell Compartmentation; D019295:Computational Biology / Q000379:methods*; D056890:Eukaryota / Q000378:metabolism; D006801:Humans; D021381:Protein Transport; D011506:Proteins / Q000378:metabolism*; D012984:Software; D014780:Viruses / Q000378:metabolism
chemical_list: D011506:Proteins