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

NucPred

Fetching P34158 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MQKSPLEKASFISKLFFSWTTPILRKGYRHHLELSDIYQAPSSDSADHLS    50
  51  EKLEREWDREQASKKKPQLIHALRRCFVWRFVFYGVLLYLGEVTKAVQPV   100
 101  LLGRIIASYDPDNTEERSIAIYLGIGLCLLFIVRTLLLHPAIFGLHHIGM   150
 151  QMRIAMFSLIYKKTLKLSSRVLDKISIGQLISLLSNNLNKFDEGLALAHF   200
 201  IWIAPLQVVLLMGLLWDLLQFSAFCGLGLLIVLVIFQAILGKMMVKYRDK   250
 251  RAAKINERLVITSEVIDNIYSVKAYCWESAMEKIIESLREEELKMTRRSA   300
 301  YMRFFTSSAFFFSGFFVVFLSVLPYTVINGIVLRKIFTTISFCIVLRMSV   350
 351  TRQFPTAVQIWYDSLGMIRKIQDFLQTQEYKVLEYNLMFTGLVMENVTAF   400
 401  WEEGFQELLEKVQLNNDDRKTSNGENHLSFSHLCLVGNPVLKNINLNIKK   450
 451  GEMLAITGSTGAGKTSLLMLILGELEASEGIIKHSGRVSFSSQISWIMPG   500
 501  TIKENIIFGVSYDEYRYKSVVKACQLQEDITKFAEQDNTVLGEGGVTLSG   550
 551  GQRARISLARAVYKDADLYLLDSPFGYLDVLTEEQIFESCVCKLMASKTR   600
 601  ILVTSKMEQLKKADKILILHEGSSYFYGTFSELQSLRPDFSSKLMGYDTF   650
 651  DQFTEERRSSILTETLRRFSVDDASTTWNKAKQSFRQTGEFGEKRKNSIL   700
 701  SSFSSVKKISIVQKTPLSIEGESDDLQERRLSLVPDSEHGEAALPRSNMI   750
 751  TAGPTFPGRRRQSVLDLMTFTPSSVSSSLQRTRASIRKISLAPRISLKEE   800
 801  DIYSRRLSQDSTLNITEEINEEDLKECFFDDMVKIPTVTTWNTYLRYFTL   850
 851  HRGLFAVLIWCVLVFLVEVAASLFVLWLLKNNPVNGGNNGTKIANTSYVV   900
 901  VITSSSFYYIFYIYVGVADTLLALSLFRGLPLVHTLITASKILHRKMLHS   950
 951  ILHAPMSTFNKLKAGGILNRFSKDIAILDDFLPLTIFDFIQLLFIVVGAI  1000
1001  IVVSALQPYIFLATVPGLAVFILLRAYFLHTSQQLKQLESEGRSPIFTHL  1050
1051  VTSLKGLWTLRAFRRQTYFETLFHKALNLHTANWFMYLATLRWFQMRIDM  1100
1101  IFVLFFIVVTFISILTTGEGEGTTGIILTLAMNIMSTLQWAVNSSIDTDS  1150
1151  LMRSVSRVFKFIDIQTEESICTKIMKELHSEDSPNALVIKNEHVKKCDTW  1200
1201  PSGGEMVVKDLTVKYVDDGNAILENISFSISPGQRVGLLGRTGSGKSTLL  1250
1251  SAFLRMLNIKGEIQIDGVSWNSMTLQEWRKAFGVITQKVFIFSGTFRQNL  1300
1301  DPNGKWRDEEIWKVADQVGLKSVIEQFPGQLNFTLVDGGYVLSHGHKQLM  1350
1351  CLARSVLSKAKIILLDEPSANLDPITYQVIRRVLRQAFAGCTVVLCEHRI  1400
1401  EAMLDCQRFLVIEQGNVWQYESLQALLSEKSVFQRALSSSEKMKLFHGRH  1450
1451  SSKQKPRTQITAVKEETEEEVQETRL                          1476

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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