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

NucPred

Fetching P32492 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  MSFEVGTKCWYPHKEQGWIGGEVTKNDFFEGTFHLELKLEDGETVSIETN    50
  51  SFENDDDHPTLPVLRNPPILESTDDLTTLSYLNEPAVLHAIKKRYMNGQI   100
 101  YTYSGIVLIAANPFDKVDHLYSREMIQNYSSKRKDELEPHLFAIAEEAYR   150
 151  FMVHEKANQTVVVSGESGAGKTVSAKYIMRYFASVQESNNREGEVEMSQI   200
 201  ESQILATNPIMEAFGNAKTTRNDNSSRFGKYLQILFDENTTIRGSKIRTY   250
 251  LLEKSRLVYQPETERNYHIFYQILEGLPEPVKQELHLSSPKDYHYTNQGG   300
 301  QPNIAGIDEAREYKITTDALSLVGINHETQLGIFKILAGLLHIGNIEMKM   350
 351  TRNDASLSSEEQNLQIACELLGIDPFNFAKWIVKKQIVTRSEKIVTNLNY   400
 401  NQALIARDSVAKFIYSTLFDWLVDNINKTLYDPELDQQDHVFSFIGILDI   450
 451  YGFEHFEKNSFEQFCINYANEKLQQEFNQHVFKLEQEEYVKEEIEWSFIE   500
 501  FSDNQPCIDLIENKLGILSLLDEESRLPSGSDESWASKLYSAFNKPPSNE   550
 551  VFSKPRFGQTKFIVSHYAVDVEYEVEGFIEKNRDSVSLGHLDVFKATTNP   600
 601  IFKQILDNRELRSDDAPEEQNTEKKIMIPARLSQKKPTLGSMFKKSLGEL   650
 651  MAIINSTNVHYIRCIKPNSEKKPWEFDNLMVLSQLRACGVLETIRISCAG   700
 701  FPSRWTFDEFVQRYFLLTDYSLWSGILYNPDLPKEAIVNFCQSILDATIS   750
 751  DSAKYQIGNTKIFFKAGMLAFLEKLRTNKMNEICIIIQKKIRARYYRLQY   800
 801  LQTMESIKKCQSQIRSLLVRTRVDHELKTRAAILLQTNIRALWKREYYRA   850
 851  AIGQIIKLQCTCKRKLILDSVNRKFMLMAAVIIQSYIRSYGHKTDYRTLK   900
 901  RSSILVQSAMRMQLARRRYIVLQKEVEERNIRASYGIGLLEEAIEFKNSF   950
 951  ILNLEMLNDSYTRLTQLLQGDLSNIPSKQRQEYETIVNGYNDKISKLKTL  1000
1001  QVEIMNTLNKKNALKERKKKQSSLIQSHMQSLAAIKGNKPSRLSDEVKSM  1050
1051  KQELAFIENVIAQDFTTTYSANKNDKVKGLGIAGQQVKPKLVNVIRRESG  1100
1101  NPDLLELLMDLNCYTLEVTEGYLKKVNVTEVNGDNVLGPIHVITTVVSSL  1150
1151  VRNGLLIQSSKFISKVLLTVESIVMSLPKDETMLGGIFWLSNLSRLPAFA  1200
1201  ANQKTLYEANGGDEKDKLTLIYLNDLENETLKVFDKIYSTWLVKFMKHAS  1250
1251  AHIEIFDMVLNEKLFKNSGDEKFAKLFTFLNEFDAVLCKFQVVDSMHTKI  1300
1301  FNDTLKYLNVMLFNDLITKCPALNWKYGYEVDRNIERLVSWFEPRIEDVR  1350
1351  PNLIQIIQAVKILQLKISNLNEFKLLFDFWYALNPAQIQAILLKYKPANK  1400
1401  GEAGVPNEILNYLANVIKRENLSLPGKMEIMLSAQFDSAKNHLRYDTSAI  1450
1451  TQNSNTEGLATVSKIIKLDRK                               1471

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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