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

NucPred

Fetching P53675 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MAQILPVRFQEHFQLQNLGINPANIGFSTLTMESDKFICIREKVGEQAQV    50
  51  TIIDMSDPMAPIRRPISAESAIMNPASKVIALKAGKTLQIFNIEMKSKMK   100
 101  AHTMAEEVIFWKWVSVNTVALVTETAVYHWSMEGDSQPMKMFDRHTSLVG   150
 151  CQVIHYRTDEYQKWLLLVGISAQQNRVVGAMQLYSVDRKVSQPIEGHAAA   200
 201  FAEFKMEGNAKPATLFCFAVRNPTGGKLHIIEVGQPAAGNQPFVKKAVDV   250
 251  FFPPEAQNDFPVAMQIGAKHGVIYLITKYGYLHLYDLESGVCICMNRISA   300
 301  DTIFVTAPHKPTSGIIGVNKKGQVLSVCVEEDNIVNYATNVLQNPDLGLR   350
 351  LAVRSNLAGAEKLFVRKFNTLFAQGSYAEAAKVAASAPKGILRTRETVQK   400
 401  FQSIPAQSGQASPLLQYFGILLDQGQLNKLESLELCHLVLQQGRKQLLEK   450
 451  WLKEDKLECSEELGDLVKTTDPMLALSVYLRANVPSKVIQCFAETGQFQK   500
 501  IVLYAKKVGYTPDWIFLLRGVMKISPEQGLQFSRMLVQDEEPLANISQIV   550
 551  DIFMENSLIQQCTSFLLDALKNNRPAEGLLQTWLLEMNLVHAPQVADAIL   600
 601  GNKMFTHYDRAHIAQLCEKAGLLQQALEHYTDLYDIKRAVVHTHLLNPEW   650
 651  LVNFFGSLSVEDSVECLHAMLSANIRQNLQLCVQVASKYHEQLGTQALVE   700
 701  LFESFKSYKGLFYFLGSIVNFSQDPDVHLKYIQAACKTGQIKEVERICRE   750
 751  SSCYNPERVKNFLKEAKLTDQLPLIIVCDRFGFVHDLVLYLYRNNLQRYI   800
 801  EIYVQKVNPSRTPAVIGGLLDVDCSEEVIKHLIMAVRGQFSTDELVAEVE   850
 851  KRNRLKLLLPWLESQIQEGCEEPATHNALAKIYIDSNNSPECFLRENAYY   900
 901  DSSVVGRYCEKRDPHLACVAYERGQCDLELIKVCNENSLFKSEARYLVCR   950
 951  KDPELWAHVLEETNPSRRQLIDQVVQTALSETRDPEEISVTVKAFMTADL  1000
1001  PNELIELLEKIVLDNSVFSEHRNLQNLLILTAIKADRTRVMEYISRLDNY  1050
1051  DALDIASIAVSSALYEEAFTVFHKFDMNASAIQVLIEHIGNLDRAYEFAE  1100
1101  RCNEPAVWSQLAQAQLQKDLVKEAINSYIRGDDPSSYLEVVQSASRSNNW  1150
1151  EDLVKFLQMARKKGRESYIETELIFALAKTSRVSELEDFINGPNNAHIQQ  1200
1201  VGDRCYEEGMYEAAKLLYSNVSNFARLASTLVHLGEYQAAVDNSRKASST  1250
1251  RTWKEVCFACMDGQEFRFAQLCGLHIVIHADELEELMCYYQDRGYFEELI  1300
1301  LLLEAALGLERAHMGMFTELAILYSKFKPQKMLEHLELFWSRVNIPKVLR  1350
1351  AAEQAHLWAELVFLYDKYEEYDNAVLTMMSHPTEAWKEGQFKDIITKVAN  1400
1401  VELCYRALQFYLDYKPLLINDLLLVLSPRLDHTWTVSFFSKAGQLPLVKP  1450
1451  YLRSVQSHNNKSVNEALNHLLTEEEDYQGLRASIDAYDNFDNISLAQQLE  1500
1501  KHQLMEFRCIAAYLYKGNNWWAQSVELCKKDHLYKDAMQHAAESRDAELA  1550
1551  QKLLQWFLEEGKRECFAACLFTCYDLLRPDMVLELAWRHNLVDLAMPYFI  1600
1601  QVMREYLSKVDKLDALESLRKQEEHVTEPAPLVFDFDGHE            1640

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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