SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P34244 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MTGHVSKTSHVPKGRPSSLAKKAAKRAMAKVNSNPKRASGHLERVVQSVN    50
  51  DATKRLSQPDSTVSVATKSSKRKSRDTVGPWKLGKTLGKGSSGRVRLAKN   100
 101  METGQLAAIKIVPKKKAFVHCSNNGTVPNSYSSSMVTSNVSSPSIASREH   150
 151  SNHSQTNPYGIEREIVIMKLISHTNVMALFEVWENKSELYLVLEYVDGGE   200
 201  LFDYLVSKGKLPEREAIHYFKQIVEGVSYCHSFNICHRDLKPENLLLDKK   250
 251  NRRIKIADFGMAALELPNKLLKTSCGSPHYASPEIVMGRPYHGGPSDVWS   300
 301  CGIVLFALLTGHLPFNDDNIKKLLLKVQSGKYQMPSNLSSEARDLISKIL   350
 351  VIDPEKRITTQEILKHPLIKKYDDLPVNKVLRKMRKDNMARGKSNSDLHL   400
 401  LNNVSPSIVTLHSKGEIDESILRSLQILWHGVSRELITAKLLQKPMSEEK   450
 451  LFYSLLLQYKQRHSISLSSSSENKKSATESSVNEPRIEYASKTANNTGLR   500
 501  SENNDVKTLHSLEIHSEDTSTVNQNNAITGVNTEINAPVLAQKSQFSINT   550
 551  LSQPESDKAEAEAVTLPPAIPIFNASSSRIFRNSYTSISSRSRRSLRLSN   600
 601  SRLSLSASTSRETVHDNEMPLPQLPKSPSRYSLSRRAIHASPSTKSIHKS   650
 651  LSRKNIAATVAARRTLQNSASKRSLYSLQSISKRSLNLNDLLVFDDPLPS   700
 701  KKPASENVNKSEPHSLESDSDFEILCDQILFGNALDRILEEEEDNEKERD   750
 751  TQRQRQNDTKSSADTFTISGVSTNKENEGPEYPTKIEKNQFNMSYKPSEN   800
 801  MSGLSSFPIFEKENTLSSSYLEEQKPKRAALSDITNSFNKMNKQEGMRIE   850
 851  KKIQREQLQKKNDRPSPLKPIQHQELRVNSLPNDQGKPSLSLDPRRNISQ   900
 901  PVNSKVESLLQGLKFKKEPASHWTHERGSLFMSEHVEDEKPVKASDVSIE   950
 951  SSYVPLTTVATSSRDPSVLAESSTIQKPMLSLPSSFLNTSMTFKNLSQIL  1000
1001  ADDGDDKHLSVPQNQSRSVAMSHPLRKQSAKISLTPRSNLNANLSVKRNQ  1050
1051  GSPGSYLSNDLDGISDMTFAMEIPTNTFTAQAIQLMNNDTDNNKINTSPK  1100
1101  ASSFTKEKVIKSAAYISKEKEPDNSDTNYIPDYTIPNTYDEKAINIFEDA  1150
1151  PSDEGSLNTSSSESDSRASVHRKAVSIDTMATTNVLTPATNVRVSLYWNN  1200
1201  NSSGIPRETTEEILSKLRLSPENPSNTHMQKRFSSTRGSRDSNALGISQS  1250
1251  LQSMFKDLEEDQDGHTSQADILESSMSYSKRRPSEESVNPKQRVTMLFDE  1300
1301  EEEESKKVGGGKIKEEHTKLDNKISEESSQLVLPVVEKKENANNTENNYS  1350
1351  KIPKPSTIKVTKDTAMESNTQTHTKKPILKSVQNVEVEEAPSSDKKNWFV  1400
1401  KLFQNFSSHNNATKASKNHVTNISFDDAHMLTLNEFNKNSIDYQLKNLDH  1450
1451  KFGRKVVEYDCKFVKGNFKFKIKITSTPNASTVITVKKRSKHSNTSSNKA  1500
1501  FEKFNDDVERVIRNAGRS                                  1518

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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