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

NucPred

Fetching O60309 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MTSAQCPALACVMSPLRFWGPWPLLMWQLLWLLVKEAQPLEWVKDPLQLT    50
  51  SNPLGPPEPWSSHSSHFPRESPHAPTLPADPWDFDHLGPSASSEMPAPPQ   100
 101  ESTENLVPFLDTWDSAGELPLEPEQFLASQQDLKDKLSPQERLPVSPKKL   150
 151  KKDPAQRWSLAEIIGIIHQLSTPQSQKQTLQNEYSSTDTPYPGSLPPELR   200
 201  VKSDEPPGPSEQVGPSQFHLEPETQNPETLEDIQSSSLQQEAPAQLPQLL   250
 251  EEEPSSMQQEAPALPPESSMESLTLPNHEVSVQPPGEDQAYYHLPNITVK   300
 301  PADVEVTITSEPTNETESSQAQQETPIQFPEEVEPSATQQEAPIEPPVPP   350
 351  MEHELSISEQQQPVQPSESSREVESSPTQQETPGQPPEHHEVTVSPPGHH   400
 401  QTHHLASPSVSVKPPDVQLTIAAEPSAEVGTSLVHQEATTRLSGSGNDVE   450
 451  PPAIQHGGPPLLPESSEEAGPLAVQQETSFQSPEPINNENPSPTQQEAAA   500
 501  EHPQTAEEGESSLTHQEAPAQTPEFPNVVVAQPPEHSHLTQATVQPLDLG   550
 551  FTITPESMTEVELSPTMKETPTQPPKKVVPQLRVYQGVTNPTPGQDQAQH   600
 601  PVSPSVTVQLLDLGLTITPEPTTEVGHSTPPKRTIVSPKHPEVTLPHPDQ   650
 651  VQTQHSHLTRATVQPLDLGFTITPKSMTEVEPSTALMTTAPPPGHPEVTL   700
 701  PPSDKGQAQHSHLTQATVQPLDLELTITTKPTTEVKPSPTTEETSTQLPD   750
 751  LGLAIIPEPTTETGHSTALEKTTAPRPDRVQTLHRSLTEVTGPPTELEPA   800
 801  QDSLVQSESYTQNKALTAPEEHKASTSTNICELCTCGDEMLSCIDLNPEQ   850
 851  RLRQVPVPEPNTHNGTFTILNFQGNYISYIDGNVWKAYSWTEKLILRENN   900
 901  LTELHKDSFEGLLSLQYLDLSCNKIQSIERHTFEPLPFLKFINLSCNVIT   950
 951  ELSFGTFQAWHGMQFLHKLILNHNPLTTVEDPYLFKLPALKYLDMGTTLV  1000
1001  PLTTLKNILMMTVELEKLIVPSHMACCLCQFKNSIEAVCKTVKLHCNSAC  1050
1051  LTNTTHCPEEASVGNPEGAFMKVLQARKNYTSTELIIEPEEPSDSSGINL  1100
1101  SGFGSEQLDTNDESDVTSTLSYILPYFSAVNLDVKSLLLPFIKLPTTGNS  1150
1151  LAKIQTVGKNRQRLNRVLMGPRSIQKRHFKEVGRQSIRREQGAQASVENT  1200
1201  AEEKRLGSPAPRELKQPHTQQGPEKLAGNAVYTKPSFTQEHKAAVSVLKP  1250
1251  FSKGAPSTSSPAKALPQVRDRWKDLTHAISILESAKARVTNMKTSKPIVH  1300
1301  SRKKYRFHKTRSRMTHRTPKVKKSPKVRKKSYLSRLMLSNRLPFSAAKSL  1350
1351  INSPSQGAFSSLRDLSPQENPFLEVSAPSEHFIENNNTKDTTARNAFEEN  1400
1401  VFMENTNMPEGTISENTNYNHPPEADSAGTAFNLGPTVKQTETKWEYNNV  1450
1451  GTDLSPEPKSFNYPLLSSPGDQFEIQLTQQLQSVIPNNNVRRLIAHVIRT  1500
1501  LKMDCSGAHVQVTCAKLVSRTGHLMKLLSGQQEVKASKIEWDTDQWKTEN  1550
1551  YINESTEAQSEQKEKSLEFTKELPGYGYTKKLILALIVTGILTILIILLC  1600
1601  LIEICCHRRSLQEDEEGFSRDSEAPTEEESEALP                  1634

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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