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

NucPred

Fetching Q9PTD7 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MERDIYGDMADQHIPVGQGVQIRFIGDLKENGKPRGKRSKQDSYGVAVRV    50
  51  QGIDGQPFVVLNSGDKAKSSFGVQIKSQEPYLNASNTSPPNYQNYSSKPR   100
 101  GPSRSISSESELPENPYGSRGYRPSSSHYSSASDEEQKPRGNIRGSDGLS   150
 151  SLPRPLQASRREELRRSQSHSSLLEPDVEESYDYDHHYSERSSTLDTTYS   200
 201  QSSRDSAWSRSSQKKIDNGDYPSLGYRSATSQQSTSVSNKTKKNGLSTSS   250
 251  PSNQSNEDIDTKPLSSVDSLINKFDIKGQVRGRTARRSQALKDERKRSQS   300
 301  LDGRKNYHDTADSREIIVEKQNEVQTMREPVNASNRSFNRQTLERGDISK   350
 351  TRLTKEWLDQDREEPVILKQQRTVQSEFQLKSTPDLLRDQQPDGSDPTRE   400
 401  MIFGILREGSLESENTLRKKTSILLEKLPSLQVQPGEDTISLGSQKKELE   450
 451  RKVAELQRQLDDEMKQRMKLETSQGRPKAGMQRLEIELEESKEECSRLKE   500
 501  LYEKKKNELSAMSQELMEVRMGKEQVETKLRTMEDKLMDSKEELSHLRAK   550
 551  GGTSPDKLALLKELEEVQDELDEVLQIRQKQEELLRQKDRELTALKGALK   600
 601  DEVANHDKDLDRVREQYQNDMQQLRKNMDNVSQDQLSLESERQKINQVVR   650
 651  NLQRELEESSDEISQWKEMFQKNKEELRSTKQELLQMKLEKEESEDELKE   700
 701  TRDRFSLLQSELAQVKKGSVDPGEVASVRKELQRVQDQLKQLSVDKQKVE   750
 751  ENLQQREREMSALKGTLKEEVSGRDRETVRLREQLQSEVMHVKKENEGLA   800
 801  KESRRIQDQLKQVLLEKQRHEETVHQRERELSVLKGALKDEVSGRDRETE   850
 851  KLRERLEQDALMTKRSYEELVKINKRLESEKTDLERVRQVIENNLQESRE   900
 901  ENDDLRRKILGLEAQLKETNTFCDDLQRAESRLKDKINKLEAERKRMEDS   950
 951  LGEVADQEQELAFVKRDLESKLDEAQRSLKRLSLEYEELQECYQEEMKQK  1000
1001  DHLKKTKNELEEQKRLLDKSMDKLTRELDNMSNESRGSLQLLQTQLEEYR  1050
1051  EKSRKEIGEAQKQAKEKTAEAERHQFNSSRMQEEVQKLKLALQELQVEKE  1100
1101  TVELDKQMISQRLQSLEQDIESKKRVQDDRSRQVKVLEDKLKRMEAELDE  1150
1151  EKNTVELLTDRVNRSRDQMEQQRAELNQERSRGQDLECDKISLERQNKEL  1200
1201  KNRLASMEGQQKPSVNVSHLEAKLQEIQERLQLEEREKATLLSTNRKLER  1250
1251  KLKELNIQLEDERLQVNDQKDQLNLRVKALKRQVDEAEEEIERLEGLRKK  1300
1301  AVREMEEQQEINEQLQTRVKVMEKESKRKPIRPAHDDDLSSDGEFGGPYD  1350
1351  PSSITSLLTESNLQTSSC                                  1368

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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