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

NucPred

Fetching P42787 from www.uniprot.org...

The NucPred score for your sequence is 0.27 (see score help below)

   1  MPTLGLLFASIGIAVLAMGVPHCRGYTIKEDESFLQQPHYASQEQLEDLF    50
  51  AGLEKAYPNQAKVHFLGRSLEGRNLLALQISRNTRSRNLLTPPVKYIANM   100
 101  HGDETVGRQLLVYMAQYLLGNHERISDLGQLVNSTDIYLVPTMNPDGYAL   150
 151  SQEGNCESLPNYVGRGNAANIDLNRDFPDRLEQSHVHQLRAQSRQPETAA   200
 201  LVNWIVSKPFVLSANFHGGAVVASYPYDNSLAHNECCEESLTPDDRVFKQ   250
 251  LAHTYSDNHPIMRKGNNCNDSFSGGITNGAHWYELSGGMQDFNYAFSNCF   300
 301  ELTIELSCCKYPAASTLPQEWQRNKASLLQLLRQAHIGIKGLVTDASGFP   350
 351  IADANVYVAGLEEKPMRTSKRGEYWRLLTPGLYSVHASAFGYQTSAPQQV   400
 401  RVTNDNQEALRLDFKLAPVETNFDGNFRKVKVERSEPPQKLKKQFNGFLT   450
 451  PTKYEHHNFTAMESYLRAISSSYPSLTRLYSIGKSVQGRDLWVLEIFATP   500
 501  GSHVPGVPEFKYVANMHGNEVVGKELLLILTKYMLERYGNDDRITKLVNG   550
 551  TRMHFLYSMNPDGYEISIEGDRTGGVGRANAHGIDLNRNFPDQYGTDRFN   600
 601  KVTEPEVAAVMNWTLSLPFVLSANLHGGSLVANYPFDDNENDFNDPFMRL   650
 651  RNSSINGRKPNPTEDNALFKHLAGIYSNAHPTMYLGQPCELFQNEFFPDG   700
 701  ITNGAQWYSVTGGMQDWNYVRAGCLELTIEMGCDKFPKAAELSRYWEDHR   750
 751  EPLLQFIEQVHCGIHGFVHSTIGTPIAGAVVRLDGANHSTYSQVFGDYWK   800
 801  LALPGRHNLTVLGDNYAPLRMEVEVPDVHPFEMRMDITLMPDDPQHWASA   850
 851  NDFRIIENVVNTRYHTNPQVRARLAELENQNGQIASFGYADSEFGTIFNY   900
 901  LKMTSDIGEPEEHKYKLLVVSSLYDTTAPLGREILLNLIRHLVEGFKLQD   950
 951  TSVVELLKRSVIYFLPQTSKFQNVFDMYNSNTSICDPVLGDELAERILGP  1000
1001  ETDQAKDVFLQFLRSERFDLMLTFGAGNSDLNYPKGDSVLVKFAHRMQRT  1050
1051  EFNYSPLQCPPSATRQLHRETTERLTNMMYRIYNLPVYTLGISCCRMPHQ  1100
1101  KKIASVWRKNIDKIKNFLALVKTGVSGLVQNDKGQPLREAYVRLLEHDRI  1150
1151  INVTKNVARFQLMLPHGLYGLEVTAPNYESQMIKVDVEDGRVTELGIIRM  1200
1201  HPFTLIRGVVLELPNNDNRATTSIAGVVLDESNHPVRNAKVSVVGQTQLR  1250
1251  NFTGSMGQYRISAVPLGTITLKVEAPRHLEATRQMHLIQGGLATENVVFH  1300
1301  LKVNEHVFGLPRFLFILCASVLIIVGVIVCVLCAQFWFYRRHRGDKPYYN  1350
1351  FSLLPQRGKEQFGLEDDDGGDDGETELFRSPIKRELSQRAHLVNNQTNYS  1400
1401  FIIQAA                                              1406

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.)

Go back to the NucPred Home Page.