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

NucPred

Fetching P15215 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MKRSRWSHSGSSTARLLLIGVLFASCSTAILGAQRPPINSAGGHELRGTT    50
  51  FMPALECYDPYGRPQKCLPEFINAAYQLQIESTNTCGEQNDNHFCIQTMN   100
 101  QNHKNCEFCKYNDHNPSFLTDLHDPQSPTWWQSETMFEGIQHPNYVNLTL   150
 151  HLGKSYDITYVRILFRSPRPESFTIYKRTSESGPWIPYQFYSATCRDTYS   200
 201  LPDSRAIRKGEGEAHALCTSEYSDISPLRDGEIAFSTLEGRPSGINFERS   250
 251  GELQEWVTATDIRITLDRLNTFGDELFGDSQVLKSYFYAISDIAVGARCK   300
 301  CNGHASKCVPSTGMHGERTLVCECRHNTDGPDCDRCLPLYNDLKWKRSTS   350
 351  TEVNECKACNCNGLADKCFFDANLFNRTGHGGHCLDCRENRDGPNCERCK   400
 401  ENFYMRDDGYCVNCACDPVGSRSLQCNSHGKCQCKPGVTGDKCDRCDNNY   450
 451  YQFGPHGCQQCGCDSGGSHQNTPACDTETGICFCKENVEGRRCNECKPGF   500
 501  FNLDKNNRFGCTPCFCYGHTSECMTAPGYSIVSVTSNFNKFKERWTAADL   550
 551  NQREVDIKYNQYSRSIGTTAQGNEHVYFQAPDRFLGDQRASYNRDLKFKL   600
 601  QLVGQVANTGVSDVILEGAGSRISLPIFAQGNGIPDQGVKEYTFRLHEHH   650
 651  DYQWQPSQSARGFLSILSNLTAIKIRATYSVQGEAILDDVELQTAHRGAA   700
 701  GHPATWIEQCTCPEGYLGQFCESCAPGYRHSPARGGPFMPCIPCDCHGHA   750
 751  DICDSETGRCICQHNTHGDNCDQCAKGFYGNALGGTPNDCKRCPCPNDGA   800
 801  CLQINEDTVICTECPKGYFGSRCEQCSDGFFGDPTGLLGEVQTCKSCDCN   850
 851  GNVDPNAVGNCNRTTGECLKCIHNTAGEHCDQCLSGHFGDPLALPHGRCD   900
 901  RCSCYEAGTEQDEQSITRCDQVTGQCQCKPNVIGRDCGECQPGYFNIRSG   950
 951  NGCENCLCDPVGSYNSTCDRYSGQCHCRPGVMGQRCDQCENYFYGFSSEG  1000
1001  CKPCECDESGSKGFQCDQNGQCPCNDNVEGRRCDRCKENKYDRHRGCIDC  1050
1051  PDCYNLVQDAADLHRAKLFNLSQTLDEIARTPVTNDDEFEAKLKAVQEKV  1100
1101  AVLAQDARDNSGDGGQTYAEVIDDLHKHLDSVREHLVSADKFQADANGEI  1150
1151  DRARQNYTILDQITENAKKELQQALDLLNDEGAQALARAKEKSVEFGQQS  1200
1201  EQISDISREARALADKLESEAQFDLKNAKDAKDAVEKAHQLAKSAIDLQL  1250
1251  KIGTELRSEVGLELSHVKQSLGTVVQTSKEALRKANEVYDTALTLLNDVN  1300
1301  RQTQPEIDISQLKKDAVAANERADELLKQITELSNSNGELFADFETEQEL  1350
1351  TEALLKRAEQQQLEDIELLERAKAAHDKATKAVEQGDNTLKEANNTYEKL  1400
1401  AGFQSDVQRSSESAEKALQTVPNIEKEIQNAESLISQAEEALDGANKNAN  1450
1451  EAKKNAQEAQLKYAEQASKDAELIRRKANETKVAARNLREEADQLNHRVK  1500
1501  LTEMDIFKLEESSTKDDNLVDDAKRKVGQAKADTQEAQKQIEKANADLTA  1550
1551  IKDELENLKDINTGDLDRLENRLATVEGEINRVNLTGRIEKYREQRTIQK  1600
1601  NLIDKYDAELRELKDEVQNIGLISKALPDSCFSRNRLEP             1639

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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