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

NucPred

Fetching P17883 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MSDIKQLLKEAKQELTNRDYEETIEISEKVLKLDPDNYFAHIFLGKALSS    50
  51  LPASNNVSSNRNLERATNHYVSAAKLVPDNLLAWKGLFLLFRTTEVVPDI   100
 101  LSYDEYFDLCGQYADALLKQEQSQVELINDIKLLKKTHPDCQKAFYQHLK   150
 151  PGSLMAETIGRHLSTPQDALLNLIKILSNIETTEIGKTLSQNRLKLKASD   200
 201  PDYQIKLNSFSWEIIKNSEIDQLYNQLVNILADDQKRSEIENQWLEYRIK   250
 251  VLKSMPLDVKKDFFTKVKEMVEDMVLVNHQSLLAWQKYFEWTDYEDLDNM   300
 301  DAPLIIKYFKKFPKDPLAMILYSWLSSKLSKYDIKSLESANKPPEGHKKT   350
 351  EKETDIKDVDETNEDEVKDRVEDEVKDRVEDEVKDQDEEAKEDEEEDLDD   400
 401  IEIGLLEEEVVTVLTENIVKCKNNILAHRILCQYYLLTKEYEAALPYIKN   450
 451  GISLIAYNIKDLGVHLPLTKREFSLDLATVYTYVDAPKDHNAALKLYDNI   500
 501  LSGDFSNIQAKMGKGIIFIERKNWKDAMTLLTQVHEQSPNNLEVLSELSW   550
 551  SKAHMGYMDEALAGLDTVIKGIKGMDLRSIDFRALNLWRQAKVYIMKHAS   600
 601  INDAKQENVKCAFKLLIQSIKILDTFAPGFSTLGDIYCHYYKDHLRAFKC   650
 651  YFKAFDLDAGDYTAAKYITETYASKPNWQAASSIASRLIKGEKAKAELRS   700
 701  NNWPFRVVGIAHLEKQEESDSIEWFQSALRVDPNDVESWVGLGQAYHACG   750
 751  RIEASIKVFDKAIQLRPSHTFAQYFKAISLCDVGEYLESLDILEKVCQEA   800
 801  ATEESFQIGLVEVLMRCSLDLYSQGFLLKSVSIAKDTIERIKIIISELKC   850
 851  ENQQVWIYLSQVLRLFIWIESKVDTLPVESLVSIFENSQFSGSEEIDSVD   900
 901  NIKIDTLLDSTTDDNVSIACKFLILASKYSVSDQKFTDIAGTVRASYWYN   950
 951  IGISELTAFITLKEPQYRDAAIFAFKKSIQLQSNTSETWIGLGIATMDIN  1000
1001  FRVSQHCFIKATALEPKATNTWFNLAMLGLKKKDTEFAQQVLNKLQSLAP  1050
1051  QDSSPWLGMALILEEQGDIIGSSKLFAHSFILSNGRSKAAQFMYAKNVLE  1100
1101  NHINNGDDERDIETVEKLTTASIALEQFFKKSPDSQFALQCALLTLERLH  1150
1151  HYENANELANRLIGILEKKFEKTQDERELFNFAIIKGQFARIHLGLGNFE  1200
1201  LSIENADLSQGIISESSDEKSMKTKISNHICLGLSYFFLNDFDQTLNQFQ  1250
1251  ELLSISKDSKHLVVLIAKVLYDVGESDTKEIALQELTEYIATSGADLLVT  1300
1301  LTIAAMSILDDKREDLSIILEELKALPLSKQIIDKHKDAPYLIEEITKRL  1350
1351  YRNDTGKQVWQRSAYFFPNNLKVWERLDKNIQRRIASNGQNKVTAEEMSK  1400
1401  LYCESKNLRSIQRGMFLCPWNVTAVKALNECF                    1432

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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