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

NucPred

Fetching P47170 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MFAKLHGKKQRPISSINSQTPRTSNTTHANSISLSSGNLIVGSNRNLRQK    50
  51  KEQFGSQQRASGRKLISNKENDDNVNNGGDNNYDNGERVHRHHIPGLKIK   100
 101  AYQAELGYHESRFSENLVMLNLVEFPDIKPGDLVELKTYHKNPSASNGDK   150
 151  KIYFIAKDFDGETKRRAKTSNVSILSGQLQTLLDLPSRSRIWIKLKPNKF   200
 201  DLQADVVEFNIKDCLLNRGDMWVLSSKLVDTCVFMDQRLAFLDSIRGTIK   250
 251  GIYRNGKKIVSGYIGEQTRIIFRSESARLIFLIQITDEMWNFEETGEQLF   300
 301  QKMVNSFFPKIFKKWKDVDTHHTITIAFAISMDLSDTSFKDLTPGESLKN   350
 351  SQDYFRIVVDQVSIIHWVDIMETLREEFMEIRKDLLNKQTDKGYSVANGR   400
 401  FSPVIKSNFLELVNFATTILTDPFKQLDLRHTTTHVMIISPGSGLFDVDY   450
 451  SLLRLTGKKLLSLEMTMDLICLSKAPLHIVPLFRYRDFENKLHHCVPLWL   500
 501  SVFFWNDHDKKSNSEWTPRCKIYDLQMMGITENELIREVDVEYLQLNKKV   550
 551  KSLSEFMNDYDKNAFEVKILCAGSNTKQSKKLNSKFDTVFENDVVVKARK   600
 601  IPATATTTHGNTKFIWRGPKVALPAIKDIQKPNVIPDLSIKTIEASFYDD   650
 651  CNTTNDKISTPTTSNNDNLEMNDSLVSVRSADNQNTSLALDSLKGLSKRN   700
 701  SLKDFTQRVITKFISNIDTSKNKKIKSTLLRDDVDNSPLGSNTPLPSSES   750
 751  KISGLKLQQKGLADENVISKRGNLIIKKNLSIFGLPSNEIMSGSPSSYLG   800
 801  SSHTRTSSKLSNMSDKAAFITEGQKSKHDDSNTYSLTQQLKHRISETWVD   850
 851  IKSPSIPVSSEFANELLPIRWKDVWPKYVARKYSKWRSFTTPAELPITIS   900
 901  DFPSKDDFDRNFIFRNHSVTLNTDQEQYNQTYKDLLRDMIYMRLLTGFQI   950
 951  CVGRQVEKIELSRESGESETVVNKYLDFNQNDAFKLYLMIDSEIHRITCS  1000
1001  SSGIIDVERYLRKDEANLFDQVPSYIPLVKTRYESSFRDAMIDPLHVKRE  1050
1051  SLNWNQIDQVLAGYGDNLIDRKWHGFRAKYVVLPTDIPPNTYSMVINGKS  1100
1101  ETLNPEEIRVEGLRRLIGSITRSRLRTEKEKKGRKTKREEIQPEVMFYTG  1150
1151  PLYNFINEQQTSLESSAINFKDSIFVNDNNLLNRNVELSKLAYQIQRGED  1200
1201  RITLVNRKWHWKKHEKCFVGSEMVNWLIRNFSDIDTREDAIKYGQKVMKE  1250
1251  GLFVHVLNKHNFLDGHYFYQFSPEYVMDTNKLEKTNSHRSTLSDPKQMLR  1300
1301  KASTGSSNDPSAMTPFSSVVPAISASNASVADAKEPSRPILMLSNSLVID  1350
1351  VDPAGKSSKQESCTVHYDRVHNPDHCFHIRLEWLTTTPKLIDDLVGNWSR  1400
1401  LCERYGLKMIEIPWEELCTIPSVNPFHSFVEIKLAINPWEDPEFKDRELF  1450
1451  AKSKFYYHVYLLKASGFLLDNRASKFLQNQDIEFDIMYSWGKPQFKYVQY  1500
1501  IHHTGAYVAELRENGCLFLAPNNIYISRVNPGNIIGKIHSASSSSLDAQK  1550
1551  VILNFKSTCLDYQKLRSIFLDAKEMWITGKIVED                  1584

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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