Finding nuclear localization signals

By Murat Cokol, Rajesh Nair, Burkhard Rost. EMBO Reports, 2000

730 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2875a97c8d8030582b54bf63801e5a6e4f9ea0bb

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Citations in the corpus

NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction (2009, methodology): “One method, Pre-dictNLS [8], employs a database of regular expressions to predict the various types of NLSs.”
Lessons from the Genome Sequence of Neurospora crassa: Tracing the Path from Genomic Blueprint to Multicellular Organism (2004, background): “Three cyclophilins of Neurospora are predicted to be nuclear (PredictNLS [165]); one contains an RNA binding domain, one contains a WD40 repeat, while the third contains a U-box (ring finger) domain.”
MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction (2009, background): “They are based either on the detection of sequence-coded sorting signals like N-terminal targeting peptides [3-11] and nuclear localization signals (NLS) [11] or use the fact that the amino acid composition of a protein is correlated with its localization [12].”
Systematic identification of cell cycle-dependent yeast nucleocytoplasmic shuttling proteins by prediction of composite motifs (2009, methodology): “In contrast, Dna2, which was predicted ThepredictionaccuraciesofthecNLSMapper,PSORTII(http://psort.nibb.ac.jp/ form2.html), and PredictNLS (http://cubic.bioc.columbia.edu/predictNLS/) programs were determined by using test peptide sequences derived from synthetic NLS mutants (see Figs.”
Review: protein secondary structure prediction continues to rise. (2001, background): “For example, we have not predicted regular secondary structure for any of the known nuclear localization signals ( 128 ).”
PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors (2013, background): “Nuclear localization signals were predicted by PredictNLS (24).”
The PredictProtein server (2003, background): “LOCi is a hierarchical system that predicts sub-cellular localization through a variety of sources, namely through homology to proteins of experimentally known localization [LOChom (27,40)], through Swiss-Prot keyword searches [LOCkey(41)],localizationsignals[SignalP(42)],TargetP(43), PredictNLS ( 2”
Locating proteins in the cell using TargetP, SignalP and related tools (2007, background): “Some of them are called bipartite NLSs, as they consist of two basic regions separated by a spacer of approximately ten residue”