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

NucPred

Fetching P29375 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MAGVGPGGYAAEFVPPPECPVFEPSWEEFTDPLSFIGRIRPLAEKTGICK    50
  51  IRPPKDWQPPFACEVKSFRFTPRVQRLNELEAMTRVRLDFLDQLAKFWEL   100
 101  QGSTLKIPVVERKILDLYALSKIVASKGGFEMVTKEKKWSKVGSRLGYLP   150
 151  GKGTGSLLKSHYERILYPYELFQSGVSLMGVQMPNLDLKEKVEPEVLSTD   200
 201  TQTSPEPGTRMNILPKRTRRVKTQSESGDVSRNTELKKLQIFGAGPKVVG   250
 251  LAMGTKDKEDEVTRRRKVTNRSDAFNMQMRQRKGTLSVNFVDLYVCMFCG   300
 301  RGNNEDKLLLCDGCDDSYHTFCLIPPLPDVPKGDWRCPKCVAEECSKPRE   350
 351  AFGFEQAVREYTLQSFGEMADNFKSDYFNMPVHMVPTELVEKEFWRLVSS   400
 401  IEEDVIVEYGADISSKDFGSGFPVKDGRRKILPEEEEYALSGWNLNNMPV   450
 451  LEQSVLAHINVDISGMKVPWLYVGMCFSSFCWHIEDHWSYSINYLHWGEP   500
 501  KTWYGVPSHAAEQLEEVMRELAPELFESQPDLLHQLVTIMNPNVLMEHGV   550
 551  PVYRTNQCAGEFVVTFPRAYHSGFNQGYNFAEAVNFCTADWLPIGRQCVN   600
 601  HYRRLRRHCVFSHEELIFKMAADPECLDVGLAAMVCKELTLMTEEETRLR   650
 651  ESVVQMGVLMSEEEVFELVPDDERQCSACRTTCFLSALTCSCNPERLVCL   700
 701  YHPTDLCPCPMQKKCLRYRYPLEDLPSLLYGVKVRAQSYDTWVSRVTEAL   750
 751  SANFNHKKDLIELRVMLEDAEDRKYPENDLFRKLRDAVKEAETCASVAQL   800
 801  LLSKKQKHRQSPDSGRTRTKLTVEELKAFVQQLFSLPCVISQARQVKNLL   850
 851  DDVEEFHERAQEAMMDETPDSSKLQMLIDMGSSLYVELPELPRLKQELQQ   900
 901  ARWLDEVRLTLSDPQQVTLDVMKKLIDSGVGLAPHHAVEKAMAELQELLT   950
 951  VSERWEEKAKVCLQARPRHSVASLESIVNEAKNIPAFLPNVLSLKEALQK  1000
1001  AREWTAKVEAIQSGSNYAYLEQLESLSAKGRPIPVRLEALPQVESQVAAA  1050
1051  RAWRERTGRTFLKKNSSHTLLQVLSPRTDIGVYGSGKNRRKKVKELIEKE  1100
1101  KEKDLDLEPLSDLEEGLEETRDTAMVVAVFKEREQKEIEAMHSLRAANLA  1150
1151  KMTMVDRIEEVKFCICRKTASGFMLQCELCKDWFHNSCVPLPKSSSQKKG  1200
1201  SSWQAKEVKFLCPLCMRSRRPRLETILSLLVSLQKLPVRLPEGEALQCLT  1250
1251  ERAMSWQDRARQALATDELSSALAKLSVLSQRMVEQAAREKTEKIISAEL  1300
1301  QKAAANPDLQGHLPSFQQSAFNRVVSSVSSSPRQTMDYDDEETDSDEDIR  1350
1351  ETYGYDMKDTASVKSSSSLEPNLFCDEEIPIKSEEVVTHMWTAPSFCAEH  1400
1401  AYSSASKSCSQGSSTPRKQPRKSPLVPRSLEPPVLELSPGAKAQLEELMM  1450
1451  VGDLLEVSLDETQHIWRILQATHPPSEDRFLHIMEDDSMEEKPLKVKGKD  1500
1501  SSEKKRKRKLEKVEQLFGEGKQKSKELKKMDKPRKKKLKLGADKSKELNK  1550
1551  LAKKLAKEEERKKKKEKAAAAKVELVKESTEKKREKKVLDIPSKYDWSGA  1600
1601  EESDDENAVCAAQNCQRPCKDKVDWVQCDGGCDEWFHQVCVGVSPEMAEN  1650
1651  EDYICINCAKKQGPVSPGPAPPPSFIMSYKLPMEDLKETS            1690

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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