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

NucPred

Fetching P47102 from www.uniprot.org...

The NucPred score for your sequence is 0.56 (see score help below)

   1  MHDVPMETVLAVNPATMIVKECINLCSAMNKQSRDKSQTSVAALLGGGSD    50
  51  IFLSQSDSFVDSFHNLPTSSYHDPLISGLVQLRLKINDLKGLDSLNALEL   100
 101  LKPFLEIVSASSVSGYTTSLALDSLQKVFTLKIINKTFNDIQIAVRETVV   150
 151  ALTHCRFEASKQISDDSVLLKVVTLLRDIITSSFGDYLSDTIIYDVLQTT   200
 201  LSLACNTQRSEVLRKTAEVTIAGITVKLFTKLKLLDPPTKTEKYINDESY   250
 251  TDNNLKDDIIGTTTSDNDLSSTDDDSAVADDNKNEKPVQQVIREQENDEE   300
 301  TAEKAENVEPNYGITVIKDYLGLLLSLVMPENRMKHTTSAMKLSLQLINA   350
 351  AIEISGDKFPLYPRLFSLISDPIFKSVLFIIQSSTQYSLLQATLQLFTSL   400
 401  VVILGDYLPMQIELTLRRIFEILEDTTISGDVSKQKPPAIRELIIEQLSI   450
 451  LWIHSPAFFLQLFVNFDCNLDRSDLSIDFIKELTKFSLPAAAVNTSNNIP   500
 501  PICLEGVLSLIENIYNDLQRFDRAEFVKNQKEIDILKQRDRKTEFILCVE   550
 551  TFNEKAKKGIQMLIEKGFIDSDSNRDIASFLFLNNGRLNKKTIGLLLCDP   600
 601  KKTSLLKEFIDLFDFKGLRVDEAIRILLTKFRLPGESQQIERIVEAFSSK   650
 651  YSADQSNDKVELEDKKAGKNGSESMTEDDIIHVQPDADSVFVLSYSIIML   700
 701  NTDSHNPQVKDHMTFDDYSNNLRGCYNGKDFPRWYLHKIYTSIKVKEIVM   750
 751  PEEHHGNERWFEDAWNNLISSTSVMTEMQRDFTNPISKLAQIDILQYEKA   800
 801  IFSNVRDIILKTLFKIFTVASSDQISLRILDAISKCTFINYYFSFDQSYN   850
 851  DTVLHLGEMTTLAQSSAKAVELDVDSIPLVEIFVEDTGSKISVSNQSIRL   900
 901  GQNFKAQLCTVLYFQIIKEISDPSIVSTRLWNQIVQLILKLFENLLMEPN   950
 951  LPFFTNFHSLLKLPELPLPDPDISIRKAKMSRSLLSTFASYLKGDEEPSE  1000
1001  EDIDFSIKAFECVKASHPLSSVFENNQLVSPKMIETLLSSLVIEKTSENS  1050
1051  PYFEQELLFLLEISIILISEASYGQEFGALIADHMINISNLDGLSKEAIA  1100
1101  RLASYKMFLVSRFDNPRDILSDLIEHDFLVKNEIFNTKYYESEWGKQVIN  1150
1151  DLFTHLNDVKYNERALKNVKFWNFLRILISAKDRQFAVYTFLEKYIQNGD  1200
1201  IFVDDGNFMNILSLLDEMSCAGAVGTKWEQNYENSVEDGCEAPESNPYRS  1250
1251  IIDLSSRSINITADLLSTVGRSNSALNKNEIIAAIQGLAHQCLNPCDELG  1300
1301  MQALQALENILLSRASQLRTEKVAVDNLLETGLLPIFELDEIQDVKMKRI  1350
1351  TSILSVLSKIFLGQLVEGVTSNETFLRVLNVFNKYVDDPTVERQLQELII  1400
1401  SKREIEKE                                            1408

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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