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

NucPred

Fetching P19615 from www.uniprot.org...

The NucPred score for your sequence is 0.53 (see score help below)

   1  MRAAILFCLVASSMAVPSGSLGSRPGTCPPQPSDQVMIEATRCSYVYGLT    50
  51  WDWNCNSQGQENYKCCQYENDIRICVPPIPADVDEEVGVEQPSQSVDQVR   100
 101  QAIQKTQDFIRKVGLYPAPDQRRRTTPTPDTVRWCVSSRCQMTKCQRMVS   150
 151  EFTYSPNMVPRKQWKCTQATSQEQCMFWIEQGWADIMTTREGQVYSANTT   200
 201  FNLKPIAYETTINDQQPEIQILKHYQNVTFALKSSRLVNPNTFSELRDKT   250
 251  TCHAGIDMPDFDMPASFADPVCNLIKEGVIPVTGNYIESFSDFVQESCVP   300
 301  GVLNMTYNKNGTYPLSLVTLCEDQQYKYSGIKGALSCLESGKGQVTFVDQ   350
 351  KVIKKIMSDPNVRDNFQVVCRDESRPLDEEIFTDVTCHVGHTARPTIFIN   400
 401  KNNTQQKETDIKTLVVKMMELYGNTDRDVNFNIFDSSVYDCGKCQMTGKP   450
 451  LNKNLIFLEESNTMKIVDDSKVYAGEVYAAYNVCSKLVPKPRAKICVTNV   500
 501  TEYEACRRFKGIAENIPEVKKVAWGCVLANSSIECMQAVHNNTADLFKAN   550
 551  PMETFIAGKEFLLDPLMSVHRNDSVTMNHTYTRTLAVIKRSSLAKFPGLL   600
 601  SVPEGQPKYIKDLWKLKICSAGLKNFSAFHSPIGYLLANGTIPRIGSVFE   650
 651  SVNRYFQATCVPEIEPETWRLDSDLLLGREMNWGFSSLNMYNFTGQEWLL   700
 701  WNTPATWNFLTYNRKVSTGLDIKKLIELKKQNLTSHIFNQNLSSPRNVEL   750
 751  LDDLVGVEGISDLVKGVQDTIGPEGKQKMNMLRDRLSNSFPNFEAVRTLS   800
 801  DKVDIVNKMKDARQQRLQNKDHPFGNVIQETFQGHLMVDVFSKLLELRSD   850
 851  KISTLEEIISHVKTIPYLTDFKDVEITTVLKHPAIMSYVEIYFPRLSQTF   900
 901  VEPFDNVELREREFNRYTNPLWLSPKVHTYLDLVKNHQTEITKTCNSNLP   950
 951  LNFKGYEGALRCLKSGVADLASSTSRPSVTRTLRDTDLSTGWVHLQRPPP  1000
1001  SLPQRQVVEIDVNMDIAKVCNFGEVMNPVLVTAYNTSGSWRWNITKALMI  1050
1051  AHQSVALPALFGEGTVMGKDYDMLLPIAPLNQSYQPFLGSKPLRSMEAIV  1100
1101  KASSYDWFKDQTGICYGETYTNIVKQRNETCQAIVKDVTCVGTPRMKKIS  1150
1151  VGRFGAKQFKMIKMCSRPSKFVRKMADFQCDNGFGYLKPVITAVACECML  1200
1201  CEEMIEYNTSFTEDNMWSDVSNKYVLTGEQDIYRQIPIWGNNSYFYDHTL  1250
1251  NKNFELGNHSIIVEHVQTVVVERPSPGILSQVNSEVDPEVQVQMDSASLT  1300
1301  KTCETVWNGQSWLPERFQGYKTSGSCVVPETGANAKSRVDRFRQIMQRKQ  1350
1351  QLVDHHH                                             1357

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.