title: Development of a prediction system for tail-anchored proteins.
abstract: BACKGROUND
  "Tail-anchored (TA) proteins" is a collective term for transmembrane proteins with a C-terminal transmembrane domain (TMD) and without an N-terminal signal sequence. TA proteins account for approximately 3-5 % of all transmembrane proteins that mediate membrane fusion, regulation of apoptosis, and vesicular transport. The combined use of TMD and signal sequence prediction tools is typically required to predict TA proteins.
  
  
  RESULTS
  Here we developed a prediction system named TAPPM that predicted TA proteins solely from target amino acid sequences according to the knowledge of the sequence features of TMDs and the peripheral regions of TA proteins. Manually curated TA proteins were collected from published literature. We constructed hidden markov models of TA proteins as well as three different types of transmembrane proteins with similar structures and compared their likelihoods as TA proteins.
  
  
  CONCLUSIONS
  Using the HMM models, we achieved high prediction accuracy; area under the receiver operator curve values reaching 0.963. A command line tool written in Python is available at https://github.com/davecao/tappm_cli .
authors.affiliation: Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
authors.forename: Shunsuke
authors.initials: S
authors.lastname: Shigemitsu
authors.affiliation: Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
authors.forename: Wei
authors.initials: W
authors.lastname: Cao
authors.affiliation: Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
authors.forename: Tohru
authors.initials: T
authors.lastname: Terada
authors.affiliation: Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan. shimizu@bi.a.u-tokyo.ac.jp.
authors.forename: Kentaro
authors.initials: K
authors.lastname: Shimizu
mesh_terms: D006801:Humans; D008390:Markov Chains; D008565:Membrane Proteins / Q000737:chemistry*; D000072417:Protein Domains; D021382:Protein Sorting Signals; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D008565:Membrane Proteins; D021382:Protein Sorting Signals
keywords: HMMs; Machine learning; Membrane proteins; Prediction; TA proteins