title: TPpred2: improving the prediction of mitochondrial targeting peptide cleavage sites by exploiting sequence motifs.
abstract: CONCLUSIONS
  Targeting peptides are N-terminal sorting signals in proteins that promote their translocation to mitochondria through the interaction with different protein machineries. We recently developed TPpred, a machine learning-based method scoring among the best ones available to predict the presence of a targeting peptide into a protein sequence and its cleavage site. Here we introduce TPpred2 that improves TPpred performances in the task of identifying the cleavage site of the targeting peptides. TPpred2 is now available as a web interface and as a stand-alone version for users who can freely download and adopt it for processing large volumes of sequences. Availability and implementaion: TPpred2 is available both as web server and stand-alone version at http://tppred2.biocomp.unibo.it.
  
  
  BACKGROUND
  gigi@biocomp.unibo.it
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Biocomputing Group, University of Bologna, CIRI-Health Science and Technology/Department of Biology, 40126 Bologna and Department of Computer Science and Engineering, University of Bologna, 40127 Bologna, Italy.
authors: Castrense
authors: C
authors: Savojardo
authors: Biocomputing Group, University of Bologna, CIRI-Health Science and Technology/Department of Biology, 40126 Bologna and Department of Computer Science and Engineering, University of Bologna, 40127 Bologna, Italy.
authors: Pier Luigi
authors: PL
authors: Martelli
authors: Biocomputing Group, University of Bologna, CIRI-Health Science and Technology/Department of Biology, 40126 Bologna and Department of Computer Science and Engineering, University of Bologna, 40127 Bologna, Italy Biocomputing Group, University of Bologna, CIRI-Health Science and Technology/Department of Biology, 40126 Bologna and Department of Computer Science and Engineering, University of Bologna, 40127 Bologna, Italy.
authors: Piero
authors: P
authors: Fariselli
authors: Biocomputing Group, University of Bologna, CIRI-Health Science and Technology/Department of Biology, 40126 Bologna and Department of Computer Science and Engineering, University of Bologna, 40127 Bologna, Italy.
authors: Rita
authors: R
authors: Casadio
mesh_terms: D020816:Amino Acid Motifs; D001185:Artificial Intelligence; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D024101:Mitochondrial Proteins / Q000737:chemistry* / Q000378:metabolism*; D021382:Protein Sorting Signals; D059748:Proteolysis; D012984:Software; D014584:User-Computer Interface
chemical_list: D024101:Mitochondrial Proteins; D021382:Protein Sorting Signals