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

NucPred

Fetching P70298 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MVAPVLKSFQAEVVALSKRSREAEAAFLSVYKQLIEAPDPVPSFEVARTL    50
  51  DDRLQRPSFDPSGQRLQDVHIAWKRCPEPPSAREQNEGTCPTGHTPANGN   100
 101  HLPGPEDTLVTDTLLQKNEAERQKGLQEVHITLAARLGEAEEKIKVLHSA   150
 151  LKATQTELLELRRKYDEEAASKADEVGLIMTNLEKANQRAEAAQREVESL   200
 201  REQLASVNSSIRLACCSPQGPSGEKVSFALCSGPRLEAALASKDREILRL   250
 251  LKDAQQLRHSLQELEEVSANQIADLERQLAAKSEAIEKLQEKLEAQADYE   300
 301  EIKTELSILRAMKLASSTCSLPQTLAKPDDPLLVAKDVFFPTQKFLLEKP   350
 351  ALLASPEEDPSEDDSIKGSLGTEPPYPPQLPPPPGPEDPLSPSPAQPLLG   400
 401  PSLGPDGPRTFSLSPFPSLAPGERLAGDSLLSKHMMGPAAFKGETGNLLA   450
 451  FPPTFYGGAKPPSAPAASVPCPEPTGAPEAVDGAGPEEEQLDTAEIAFQV   500
 501  KEQLLKHNIGQRVFGHYVLGLSQGSVSEILARPKPWRKLTVKGKEPFIKM   550
 551  KQFLSDEQNVLALRTIQVRQRGSITPRIRTPETGSDDAIKSILEQAKKEI   600
 601  ESQKGGESKNSPASVSIPNGTASSSTSEDAIKNILEQARREMQAQQQALL   650
 651  EMESGPRGRSVPPSPPERPSPATASQNGALTCVKQEDGGGGSGSSSTVQA   700
 701  PLAVLSPAAFVQRIIRKVKSEIGDAGYFDHHWASDRGLLSRPYASVSPSL   750
 751  SSSSSYSGQPNGRAWPRGDEATIAPEDEAAMGEDEAPRVGELKAEAGAPE   800
 801  VGGGRLPYYPAYVPRTLKPTVPPLTPEQYELYMYREVDTLELTRQVKEKL   850
 851  AKNGICQRIFGEKVLGLSQGSVSDMLSRPKPWSKLTQKGREPFIRMQLWL   900
 901  SDQLGQGQGQAPTQQPSASQASPTEPTSSPSPPPSPTEPEKTSQEPLGLS   950
 951  LESSKENQQPEGRASSSLGGKPFSSSQAAGGIQEMVAMSPELDTYSITKR  1000
1001  VKEVLTDNNLGQRLFGESILGLTQGSVSDLLSRPKPWHKLSLKGREPFVR  1050
1051  MQLWLSDPHNVEKLRDMKKLEKKAYLKRRYGLIGTGSDSESPAAHSECPS  1100
1101  PCLQPQELSLMQAKKPRVVLAPAEKEALRKAYQLEPYPSQQTIELLSFQL  1150
1151  NLKTNTVINWFHNYRSRMRREMLVEGTQDDPDFDPSGGPNVLTPGHTHRE  1200
1201  PTPQSPDSETEDQKPPMKSLELQEPEGPLQRAAPDRALVKIKQEEGLEVD  1250
1251  GDSQPQDVGDPDRGQDGPKEEHTHPLGNSDLSELAPGPFLSGTPNPDCPS  1300
1301  LHNPQEKGTGEQVHSEPLSFKSTSESSCCSLEGPPNSPSVISSPDLTTCV  1350
1351  SPAPSSSAPISPSLPGAPPAKVPSTSPTGDTAAALHPSTKVNPNLQRRHE  1400
1401  KMANLNSIIYRLERAANREEVLEWEF                          1426

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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