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

NucPred

Fetching P04821 from www.uniprot.org...

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

   1  MSDTNTSIPNTSSAREAGNASQTPSISSSSNTSTTTNTESSSASLSSSPS    50
  51  TSELTSIRPIGIVVAAYDFNYPIKKDSSSQLLSVQQGETIYILNKNSSGW   100
 101  WDGLVIDDSNGKVNRGWFPQNFGRPLRDSHLRKHSHPMKKYSSSKSSRRS   150
 151  SLNSLGNSAYLHVPRNPSKSRRGSSTLSASLSNAHNAETSSGHNNTVSMN   200
 201  NSPFSAPNDASHITPQSSNFNSNASLSQDMTKSADGSSEMNTNAIMNNNE   250
 251  TNLQTSGEKAGPPLVAEETIKILPLEEIEMIINGIRSNIASTWSPIPLIT   300
 301  KTSDYKLVYYNKDLDIYCSELPLISNSIMESDDICDSEPKFPPNDHLVNL   350
 351  YTRDLRKNANIEDSSTRSKQSESEQNRSSLLMEKQDSKETDGNNNSINDD   400
 401  DNNNENNKNEFNEAGPSSLNSLSAPDLTQNIQSRVVAPSRSSILAKSDIF   450
 451  YHYSRDIKLWTELQDLTVYYTKTAHKMFLKENRLNFTKYFDLISDSIVFT   500
 501  QLGCRLMQHEIKAKSCSKEIKKIFKGLISSLSRISINSHLYFDSAFHRKK   550
 551  MDTMNDKDNDNQENNCSRTEGDDGKIEVDSVHDLVSVPLSGKRNVSTSTT   600
 601  DTLTPMRSSFSTVNENDMENFSVLGPRNSVNSVVTPRTSIQNSTLEDFSP   650
 651  SNKNFKSAKSIYEMVDVEFSKFLRHVQLLYFVLQSSVFSDDNTLPQLLPR   700
 701  FFKGSFSGGSWTNPFSTFITDEFGNATKNKAVTSNEVTASSSKNSSISRI   750
 751  PPKMADAIASASGYSANSETNSQIDLKASSAASGSVFTPFNRPSHNRTFS   800
 801  RARVSKRKKKYPLTVDTLNTMKKKSSQIFEKLNNATGEHLKIISKPKSRI   850
 851  RNLEINSSTYEQINQNVLLLEILENLDLSIFINLKNLIKTPSILLDLESE   900
 901  EFLVHAMSSVSSVLTEFFDIKQAFHDIVIRLIMTTQQTTLDDPYLFSSMR   950
 951  SNFPVGHHEPFKNISNTPLVKGPFHKKNEQLALSLFHVLVSQDVEFNNLE  1000
1001  FLNNSDDFKDACEKYVEISNLACIIVDQLIEERENLLNYAARMMKNNLTA  1050
1051  ELLKGEQEKWFDIYSEDYSDDDSENDEAIIDDELGSEDYIERKAANIEKN  1100
1101  LPWFLTSDYETSLVYDSRGKIRGGTKEALIEHLTSHELVDAAFNVTMLIT  1150
1151  FRSILTTREFFYALIYRYNLYPPEGLSYDDYNIWIEKKSNPIKCRVVNIM  1200
1201  RTFLTQYWTRNYYEPGIPLILNFAKMVVSEKIPGAEDLLQKINEKLINEN  1250
1251  EKEPVDPKQQDSVSAVVQTTKRDNKSPIHMSSSSLPSSASSAFFRLKKLK  1300
1301  LLDIDPYTYATQLTVLEHDLYLRITMFECLDRAWGTKYCNMGGSPNITKF  1350
1351  IANANTLTNFVSHTIVKQADVKTRSKLTQYFVTVAQHCKELNNFSSMTAI  1400
1401  VSALYSSPIYRLKKTWDLVSTESKDLLKNLNNLMDSKRNFVKYRELLRSV  1450
1451  TDVACVPFFGVYLSDLTFTFVGNPDFLHNSTNIINFSKRTKIANIVEEII  1500
1501  SFKRFHYKLKRLDDIQTVIEASLENVPHIEKQYQLSLQVEPRSGNTKGST  1550
1551  HASSASGTKTAKFLSEFTDDKNGNFLKLGKKKPPSRLFR             1589

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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