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

NucPred

Fetching Q00546 from www.uniprot.org...

The NucPred score for your sequence is 0.62 (see score help below)

   1  MGTDSENPVLRNVLISFNLLLLGAVLKPFECRLEVTTEPAERPAVDEEGG    50
  51  LANCSPPVKEQPMVFHHIYNINVPVDSCCSSMLRSSAEEVSSEDDRLAEY   100
 101  TEQTSDSESQVTFTHRINLPKQACKCSTSLPSLQELLSRIEMLEREVSML   150
 151  RDQCNSNCCQENAATGRLDYTLPCSGHGNFSLESCRCICSEGWAGSNCSE   200
 201  PRCPRGCSSRGVCLEGQCVCDNDYGGEDCSQLRCPAGCGSRGLCVDGECI   250
 251  CEEGFGGEDCSQPRCPRDCSGRGHCDNGTCVCAEGYAGEDCGWLRCPNAC   300
 301  SGRGVCQDGLCICEDGYGGQDCSAVAPPENLRVTGISDGSIELAWDSLGA   350
 351  ATEYVVSYQPAGPGGSQLQQRVPGDWSTITITELEPGVAYNVSIYAVISD   400
 401  VLSSPVTTKVTTNLATPQGLKFKTITETTVEVQWEPFSFPFDGWEISFIP   450
 451  KNNEGGVIAQLPSTVTTFNQTGLKPGEEYTVTVVALKDQARSPPASDSIS   500
 501  TLIDGPTQILVRDVSDTVAFVEWTPPRARVDAILLKYGLADGEGGRTTFR   550
 551  LQPPLSQYSLQALRPGARYHLAVSALRGANESQPALAQFTTEIDAPKNLR   600
 601  VGSRTPASLELTWDNSEAEAHSYRVVYSTLAGEHYHEVLVPRDTGPTTRA   650
 651  TLADLVPGTEYGIGISAVMDSQQSVPATMNARTELDSPRDLLVTASTETS   700
 701  ISLSWTKAMGPIDHYRVTFTPASGMASEVTVSRNESQLTLSELEPGTEYT   750
 751  ISIIAERGRQQSLEATVDAFTGVRPITQLHFSQLTSSSVNITWSDPSPPA   800
 801  DRLVLTYSPRDEEAPQQLALDGTRRHASLTGLRPSTEYLVSLVAVHGAVS   850
 851  SEPVTGSITTGMDAPKDLRVGNITQDSMVIYWSPPVAPFDHYRISYRAAE   900
 901  GRTDSTAIGNDATEYIMRLLQPATKYEIGVKSVRGREESEVASITTYTAM   950
 951  DAPLGVTATNITPTEALLQWNPPLMDVESYVLVLTRHTGETILVDGINQE  1000
1001  YQLTNLQPSTTYTVAMYATNGPLTSQTISTNFTTLLDPPTNLTASEVTRR  1050
1051  SALLSWVPPVGDIENYILTYRSTDGSRKELIVDAEDTWIRLEGLSETTQY  1100
1101  TVRLQAAQNAMRSGFISTTFTTGGRVFANPQDCAQHLMNGDTLSGVYTIS  1150
1151  INGDLSQRVQVFCDMSTDGGGWIVFQRRQNGLTDFFRKWADYRVGFGNLE  1200
1201  DEFWLGLDNIHKITSQGRYELRIDMRDGQEAAYAYYDKFSVGDSRSLYKL  1250
1251  RIGDYNGTSGDSLTYHQGRPFSTKDRDNDVAVTNCAMSYKGAWWYKNCHR  1300
1301  TNLNGKYGESRHSQGINWYHWKGHEFSIPFVEMKMRPYNHRNISGRKRRS  1350
1351  LQL                                                 1353

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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