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

NucPred

Fetching P19538 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MDAYALPTYFPLAYSELQFLASRRAAAVAAAATVLPGSPCINQHHPTDVS    50
  51  SSVTVPSIIPTGGTSDSIKTSIQPQICNENTLLGNAGHQHNHQPQHVHNI   100
 101  NVTGQPHDFHPAYRIPGYMEQLYSLQRTNSASSFHDPYVNCASAFHLAGL   150
 151  GLGSADFLGSRGLSSLGELHNAAVAAAAAGSLASTDFHFSVDGNRRLGSP   200
 201  RPPGGSIRASISRKRALSSSPYSDSFDINSMIRFSPNSLATIMNGSRGSS   250
 251  AASGSYGHISATALNPMSHVHSTRLQQIQAHLLRASAGLLNPMTPQQVAA   300
 301  SGFSIGHMPTSASLRVNDVHPNLSDSHIQITTSPTVTKDVSQVPAAAFSL   350
 351  KNLDDAREKKGPFKDVVPEQPSSTSGGVAQVEADSASSQLSDRCYNNVVN   400
 401  NITGIPGDVKVNSRLDEYINCGSISIPSNEYDCANADTTDIKDEPGDFIE   450
 451  TNCHWRSCRIEFITQDELVKHINNDHIQTNKKAFVCRWEDCTRGEKPFKA   500
 501  QYMLVVHMRRHTGEKPHKCTFEGCFKAYSRLENLKTHLRSHTGEKPYTCE   550
 551  YPGCSKAFSNASDRAKHQNRTHSNEKPYICKAPGCTKRYTDPSSLRKHVK   600
 601  TVHGAEFYANKKHKGLPLNDANSRLQQNNSRHNLQEHNIDSSPCSEDSHL   650
 651  GKMLGTSSPSIKSESDISSSNHHLVNGVRASDSLLTYSPDDLAENLNLDD   700
 701  GWNCDDDVDVADLPIVLRAMVNIGNGNASASTIGGSVLARQRFRGRLQTK   750
 751  GINSSTIMLCNIPESNRTFGISELNQRITELKMEPGTDAEIKIPKLPNTT   800
 801  IGGYTEDPLQNQTSFRNTVSNKQGTVSGSIQGQFRRDSQNSTASTYYGSM   850
 851  QSRRSSQSSQVSSIPTMRPNPSCNSTASFYDPISPGCSRRSSQMSNGANC   900
 901  NSFTSTSGLPVLNKESNKSLNACINKPNIGVQGVGIYNSSLPPPPSSHLI   950
 951  ATNLKRLQRKDSEYHNFTSGRFSVPSYMHSLHIKNNKPVGENEFDKAIAS  1000
1001  NARRQTDPVPNINLDPLTNISRFSTTPHSFDINVGKTNNIASSINKDNLR  1050
1051  KDLFTVSIKADMAMTSDQHPNERINLDEVEELILPDEMLQYLNLVKDDTN  1100
1101  HLEKEHQAVPVGSNVSETIASNHYREQSNIYYTNKQILTPPSNVDIQPNT  1150
1151  TKFTVQDKFAMTAVGGSFSQRELSTLAVPNEHGHAKCESFHHQSQKYMNT  1200
1201  DIGSKQQSALPSAHQRQTEKSNYNQIIDSSMTSLPELNVDSIYPRNETEN  1250
1251  IFKVHGDHDNEIQCGIISQSQMSPSTNLNNDGQFSTVNMQPITTSKLFPP  1300
1301  EPQKIVCDTQASNTSVMHLDTYQRTLEYVQSCQNWMETNNTSTNQIQSLP  1350
1351  GMPVNNTLFPDVSSSTHPYHGTNMVINDMTTSLTSLLEENRYLQMMQ     1397

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.)

Go back to the NucPred Home Page.