NucPred - Predicting nuclear localization of proteins

Bioinformatics

Volumn 23, Issue 9, 2007, Pages 1159-1160

  Brameier, Markus ^a   Krings, Andrea ^b   MacCallum, Robert M ^c  

^a AARHUS UNIVERSITY   (Denmark)

^b STOCKHOLM UNIVERSITY   (Sweden)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID SEQUENCE; ARTICLE; CELL NUCLEUS; CELLULAR DISTRIBUTION; CONTROLLED STUDY; EUKARYOTE; HUMAN; INTERNET; NUCLEAR LOCALIZATION SIGNAL; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN EXPRESSION; PROTEIN FUNCTION; PROTEIN INTERACTION; PROTEIN LOCALIZATION; SEQUENCE ALIGNMENT; VALIDATION PROCESS; ALGORITHM; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; COMPUTER PROGRAM; METABOLISM; METHODOLOGY; MOLECULAR GENETICS; SEQUENCE ANALYSIS; STRUCTURE ACTIVITY RELATION;

EUKARYOTA;

NUCLEAR PROTEIN;

ALGORITHMS; AMINO ACID SEQUENCE; CELL NUCLEUS; MOLECULAR SEQUENCE DATA; NUCLEAR PROTEINS; PATTERN RECOGNITION, AUTOMATED; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 34249846686     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm066     Document Type: Article

References (10)

1. Cokol,M. et al. (2000) Finding nuclear localization signals. EMBO Rep., 1, 411-415.
2. Emanuelsson,O. et al. (2000) Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol., 300, 1005-1016.
3. Heddad, A. et al. (2004) Evolving regular expression-based sequence classifiers for protein nuclear localization. In Proc. of EvoBIO 2004 Conf., Lect. Notes Comput. Sci., vol. 3005, pp. 31-40.
4. Hwang,S.I. et al. (2006) Systematic characterization of nuclear proteome during apoptosis: A quantitative proteomic study by differential extraction and stable isotope labeling. Mol. Cell Proieomics, 5, 1131-1145.
5. Koza,J.R. (1992) Genetic Programming: On the Programming of Computer Programs by Natural Selection. MIT Press, Cambridge, MA.
6. Krogh,A. et al. (2001) Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J. Mol. Biol., 305, 567-580.
7. Nair,R. and Rost,B. (2005) Mimicking cellular sorting improves prediction of subcellular localization. J. Mol. Biol., 348, 85-100.
8. Nakai,K. and Horton,P. (1999) PSORT: A program for detecting sorting signals in proteins and predicting their subcellular localization. Trends Biochem. Sci., 24, 34-36.
9. Pierleoni,A. et al. (2006) BaCelLo: A balanced subcellular localization predictor. Bioinformatics, 22, 408-416.
10. Reinhardt,A. and Hubbard,T. (1998) Using neural networks for prediction of the subcellular location of proteins. Nucleic Acids Res., 26 2230-2236.