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

NucPred

Fetching Q8K2X1 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MTELLQWARHHWRRLSHGRAQGEDERPYNYASLLACGGKSSRTPRPAGKH    50
  51  RVVIPHLQCFKDEYERFSGTYVNNRIRTTKYTLLNFVPRNLFEQFHRAAN   100
 101  LYFLFLVVLNWVPLVEAFQKEITMLPLVVVLTIIAIKDGLEDYRKYKIDK   150
 151  QINNLITKVYSRKEKKYIDCCWKNVTVGDFIRLSCNEIIPADMVLLFSTD   200
 201  PDGICHIETSGLDGESNLKQRQVVRGYTEQDSEVDPEKFSSRIECESPNN   250
 251  DLSRFRGFLEHANKERVGLSKENLLLRGCTIRNTEAVVGIVVYAGHETKA   300
 301  MLNNSGPRYKRSKLERRANTDVLWCVLLLIVMCLTGALGHGIWLSRYENM   350
 351  LFFNIPEPDGRVISPVLTGFYVFWTMIILLQVLIPISLYVSIEIVKLGQI   400
 401  YFIQSDVDFYNEKMDSTIQCRALNITEDLGQIQYLFSDKTGTLTENKMVF   450
 451  RRCSVAGFDYCHEENAKRLESYQEAVSEEEECTDTLGGSLSNMARPRAQG   500
 501  CRTVPSGPLGKPSAQLSGSTSAVGNGEGSGEVPHSRQAAFSSPMETDVVP   550
 551  DTRLLDKFSQLTPQLLTGLDGTAQSSPLETLYIMDFFIALAICNTVVVSA   600
 601  PNQPRQKIGLSSLGGMPIKSLEEIKNIFQKLSVRRSSSPSLASGKDSSSG   650
 651  TPCAFVSRISFFSRPKLSPPMEDESSQMDEIPQASNSACCTETEAQNRAV   700
 701  GLSVSSAEALSGPPPSASNLCYEAESPDEAALVYAARAYRCTLQSRTPEQ   750
 751  VMVDFAALGSLTFQLLHILPFDSVRKRMSVVVRHPLSKQVVVYTKGADSV   800
 801  IMELLSVAASDGTNPEQQMIIRERTQRHLDEYAKRGLRTLCVAKKVMSDT   850
 851  EYAEWLRNHFLAETSIDNREELLVESAMRLENKLTLLGATGIEDRLQEGV   900
 901  PESIEALHQAGIKIWMLTGDKQETAVNIAYACKLLEPDDKLFILNTQSQD   950
 951  ACGMLMSAILEELQKRAQVSPELASSRKNFPQPSDAQGQGRAGLVITGKT  1000
1001  LEFALQESLQRQFLELTAWCQAVICCRATPLQKSEVVKLVRNHHHVLTLP  1050
1051  IGDGANDVSMIQVADIGIGVSGQEGMQAVMASDFAISQFRHLSKLLLVHG  1100
1101  HWCYTRLSNMILYFFYKNVAYVNLLFWYQFFCGFSGTSMTDYWVLIFFNL  1150
1151  LFTSVPPIIYGVLEKDVSAETLLQLPELYRSGQRSEEYLPLTFWITLLDA  1200
1201  FYQSLVCFFVPYFTYQGSDIDIFTFGNPLNTAALFIILLHLVIESKSLTW  1250
1251  IHMLVTVGSILSYFFFALAFGALCVTCNPPSNPYGIMRKHMLDPVFYLVC  1300
1301  VLTTFVALLPRFLYRVLQGSVFPSPVLRAKYFDRLPPEERAEALKRWRGT  1350
1351  AKVNHVASKHASQSAAMSGRPTPGSSAVLAMKSATVSTVEQSTRETALDR  1400
1401  GCSEPGASKMTGSSAS                                    1416

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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