Analysis and prediction of leucine-rich nuclear export signals

Protein Engineering, Design and Selection

Volumn 17, Issue 6, 2004, Pages 527-536

  La Cour, Tanja ^a   Kiemer, Lars ^a   Mølgaard, Anne ^a   Gupta, Ramneek ^a   Skriver, Karen ^b   Brunak, Søren ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

Analysis; NES; Nuclear export signals; Prediction; Structure

Indexed keywords

ALGORITHMS; CELLS; HYDROPHOBICITY; MARKOV PROCESSES; MATHEMATICAL MODELS; NEURAL NETWORKS;

CELL CYCLES; HIDDEN MARKOVE MODELS; NUCLEAR EXPORT SIGNALS (NES);

PROTEINS;

AMINO ACID; ASPARTIC ACID; GLUTAMIC ACID; LEUCINE; PROTEIN; SERINE; VIRUS PROTEIN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CELL NUCLEUS; HYDROPHOBICITY; NUCLEAR EXPORT SIGNAL; NUCLEOTIDE SEQUENCE; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROTEIN MOTIF; PROTEIN STRUCTURE; PROTEIN TRANSPORT; RECEIVER OPERATING CHARACTERISTIC; STATISTICAL MODEL;

ACTIVE TRANSPORT, CELL NUCLEUS; ALGORITHMS; ARTIFICIAL INTELLIGENCE; ASPARTIC ACID; COMPUTATIONAL BIOLOGY; COMPUTING METHODOLOGIES; CONSENSUS SEQUENCE; DATABASES, PROTEIN; GLUTAMIC ACID; HYDROPHOBICITY; INTERNET; ISOELECTRIC POINT; LEUCINE; MARKOV CHAINS; MODELS, MOLECULAR; NEURAL NETWORKS (COMPUTER); NUCLEAR PROTEINS; PROTEIN SORTING SIGNALS; PROTEIN STRUCTURE, SECONDARY; PROTEIN STRUCTURE, TERTIARY; REPRODUCIBILITY OF RESULTS; ROC CURVE; SEQUENCE ALIGNMENT; SERINE; STRUCTURAL HOMOLOGY, PROTEIN;

NES;

EID: 8444247065     PISSN: 17410126     EISSN: None     Source Type: Journal    
DOI: 10.1093/protein/gzh062     Document Type: Article

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