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

NucPred

Fetching P58397 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MPCAQRSWLANLSVVAQLLNFGALCYGRQPQPGPVRFPDRRQEHFIKGLP    50
  51  EYHVVGPVRVDASGHFLSYGLHYPITSSRRKRDLDGSEDWVYYRISHEEK   100
 101  DLFFNLTVNQGFLSNSYIMEKRYGNLSHVKMMASSAPLCHLSGTVLQQGT   150
 151  RVGTAALSACHGLTGFFQLPHGDFFIEPVKKHPLVEGGYHPHIVYRRQKV   200
 201  PETKEPTCGLKDSVNISQKQELWREKWERHNLPSRSLSRRSISKERWVET   250
 251  LVVADTKMIEYHGSENVESYILTIMNMVTGLFHNPSIGNAIHIVVVRLIL   300
 301  LEEEEQGLKIVHHAEKTLSSFCKWQKSINPKSDLNPVHHDVAVLLTRKDI   350
 351  CAGFNRPCETLGLSHLSGMCQPHRSCNINEDSGLPLAFTIAHELGHSFGI   400
 401  QHDGKENDCEPVGRHPYIMSRQLQYDPTPLTWSKCSEEYITRFLDRGWGF   450
 451  CLDDIPKKKGLKSKVIAPGVIYDVHHQCQLQYGPNATFCQEVENVCQTLW   500
 501  CSVKGFCRSKLDAAADGTQCGEKKWCMAGKCITVGKKPESIPGGWGRWSP   550
 551  WSHCSRTCGAGVQSAERLCNNPEPKFGGKYCTGERKRYRLCNVHPCRSEA   600
 601  PTFRQMQCSEFDTVPYKNELYHWFPIFNPAHPCELYCRPIDGQFSEKMLD   650
 651  AVIDGTPCFEGGNSRNVCINGICKMVGCDYEIDSNATEDRCGVCLGDGSS   700
 701  CQTVRKMFKQKEGSGYVDIGLIPKGARDIRVMEIEGAGNFLAIRSEDPEK   750
 751  YYLNGGFIIQWNGNYKLAGTVFQYDRKGDLEKLMATGPTNESVWIQLLFQ   800
 801  VTNPGIKYEYTIQKDGLDNDVEQQMYFWQYGHWTECSVTCGTGIRRQTAH   850
 851  CIKKGRGMVKATFCDPETQPNGRQKKCHEKACPPRWWAGEWEACSATCGP   900
 901  HGEKKRTVLCIQTMVSDEQALPPTDCQHLLKPKTLLSCNRDILCPSDWTV   950
 951  GNWSECSVSCGGGVRIRSVTCAKNHDEPCDVTRKPNSRALCGLQQCPSSR  1000
1001  RVLKPNKGTISNGKNPPTLKPVPPPTSRPRMLTTPTGPESMSTSTPAISS  1050
1051  PSPTTASKEGDLGGKQWQDSSTQPELSSRYLISTGSTSQPILTSQSLSIQ  1100
1101  PSEENVSSSDTGPTSEGGLVATTTSGSGLSSSRNPITWPVTPFYNTLTKG  1150
1151  PEMEIHSGSGEEREQPEDKDESNPVIWTKIRVPGNDAPVESTEMPLAPPL  1200
1201  TPDLSRESWWPPFSTVMEGLLPSQRPTTSETGTPRVEGMVTEKPANTLLP  1250
1251  LGGDHQPEPSGKTANRNHLKLPNNMNQTKSSEPVLTEEDATSLITEGFLL  1300
1301  NASNYKQLTNGHGSAHWIVGNWSECSTTCGLGAYWRRVECSTQMDSDCAA  1350
1351  IQRPDPAKRCHLRPCAGWKVGNWSKCSRNCSGGFKIREIQCVDSRDHRNL  1400
1401  RPFHCQFLAGIPPPLSMSCNPEPCEAWQVEPWSQCSRSCGGGVQERGVFC  1450
1451  PGGLCDWTKRPTSTMSCNEHLCCHWATGNWDLCSTSCGGGFQKRTVQCVP  1500
1501  SEGNKTEDQDQCLCDHKPRPPEFKKCNQQACKKSADLLCTKDKLSASFCQ  1550
1551  TLKAMKKCSVPTVRAECCFSCPQTHITHTQRQRRQRLLQKSKEL        1594

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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