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

NucPred

Fetching Q9Y4C0 from www.uniprot.org...

The NucPred score for your sequence is 0.46 (see score help below)

   1  MSSTLHSVFFTLKVSILLGSLLGLCLGLEFMGLPNQWARYLRWDASTRSD    50
  51  LSFQFKTNVSTGLLLYLDDGGVCDFLCLSLVDGRVQLRFSMDCAETAVLS   100
 101  NKQVNDSSWHFLMVSRDRLRTVLMLDGEGQSGELQPQRPYMDVVSDLFLG   150
 151  GVPTDIRPSALTLDGVQAMPGFKGLILDLKYGNSEPRLLGSRGVQMDAEG   200
 201  PCGERPCENGGICFLLDGHPTCDCSTTGYGGKLCSEDVSQDPGLSHLMMS   250
 251  EQAREENVATFRGSEYLCYDLSQNPIQSSSDEITLSFKTWQRNGLILHTG   300
 301  KSADYVNLALKDGAVSLVINLGSGAFEAIVEPVNGKFNDNAWHDVKVTRN   350
 351  LRQVTISVDGILTTTGYTQEDYTMLGSDDFFYVGGSPSTADLPGSPVSNN   400
 401  FMGCLKEVVYKNNDIRLELSRLARIADTKMKIYGEVVFKCENVATLDPIN   450
 451  FETPEAYISLPKWNTKRMGSISFDFRTTEPNGLILFTHGKPQERKDARSQ   500
 501  KNTKVDFFAVELLDGNLYLLLDMGSGTIKVKATQKKANDGEWYHVDIQRD   550
 551  GRSGTISVNSRRTPFTASGESEILDLEGDMYLGGLPENRAGLILPTELWT   600
 601  AMLNYGYVGCIRDLFIDGRSKNIRQLAEMQNAAGVKSSCSRMSAKQCDSY   650
 651  PCKNNAVCKDGWNRFICDCTGTGYWGRTCEREASILSYDGSMYMKIIMPM   700
 701  VMHTEAEDVSFRFMSQRAYGLLVATTSRDSADTLRLELDGGRVKLMVNLD   750
 751  CIRINCNSSKGPETLYAGQKLNDNEWHTVRVVRRGKSLKLTVDDDVAEGT   800
 801  MVGDHTRLEFHNIETGIMTEKRYISVVPSSFIGHLQSLMFNGLLYIDLCK   850
 851  NGDIDYCELKARFGLRNIIADPVTFKTKSSYLSLATLQAYTSMHLFFQFK   900
 901  TTSPDGFILFNSGDGNDFIAVELVKGYIHYVFDLGNGPNVIKGNSDRPLN   950
 951  DNQWHNVVITRDNSNTHSLKVDTKVVTQVINGAKNLDLKGDLYMAGLAQG  1000
1001  MYSNLPKLVASRDGFQGCLASVDLNGRLPDLINDALHRSGQIERGCEGPS  1050
1051  TTCQEDSCANQGVCMQQWEGFTCDCSMTSYSGNQCNDPGATYIFGKSGGL  1100
1101  ILYTWPANDRPSTRSDRLAVGFSTTVKDGILVRIDSAPGLGDFLQLHIEQ  1150
1151  GKIGVVFNIGTVDISIKEERTPVNDGKYHVVRFTRNGGNATLQVDNWPVN  1200
1201  EHYPTGRQLTIFNTQAQIAIGGKDKGRLFQGQLSGLYYDGLKVLNMAAEN  1250
1251  NPNIKINGSVRLVGEVPSILGTTQTTSMPPEMSTTVMETTTTMATTTTRK  1300
1301  NRSTASIQPTSDDLVSSAECSSDDEDFVECEPSTTGGELVIPLLVEDPLA  1350
1351  TPPIATRAPSITLPPTFRPLLTIIETTKDSLSMTSEAGLPCLSDQGSDGC  1400
1401  DDDGLVISGYGSGETFDSNLPPTDDEDFYTTFSLVTDKSLSTSIFEGGYK  1450
1451  AHAPKWESKDFRPNKVSETSRTTTTSLSPELIRFTASSSSGMVPKLPAGK  1500
1501  MNNRDLKPQPDIVLLPLPTAYELDSTKLKSPLITSPMFRNVPTANPTEPG  1550
1551  IRRVPGASEVIRESSSTTGMVVGIVAAAALCILILLYAMYKYRNRDEGSY  1600
1601  QVDETRNYISNSAQSNGTLMKEKQQSSKSGHKKQKNKDREYYV         1643

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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