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

NucPred

Fetching Q23495 from www.uniprot.org...

The NucPred score for your sequence is 0.64 (see score help below)

   1  MATSLTSQLENLRTSAARHLTVEKRHVSLLFDRKEANKLSNETAHRIGVA    50
  51  GLEQMKRIDPVFDTEFANDLFSEERVDFVRSMLEKGANEELNKQIEKLLL   100
 101  ELSPYLQHFACQQVLEFLIHTYQIYSFNAETLLLTFLPFHETKVYSRLLR   150
 151  ILDFDWKRSKEWQFMQQFTKTETPIPFTSIARATLSSKHSIITCITDHIR   200
 201  HAVEIVGSDYLEIKHPILFNFHAKLLLSMFTDPEKVDEMMLAKLMPFIEN   250
 251  GIKSPMKSFRYSAMVVISQLVLTVKLKDEVLNSMCKLLITKMRSDTAAAS   300
 301  LSTLMVVFQQQNVQSLSKNTLKKLLRHEEGIDVWKILKELSERTDTTKFF   350
 351  NVLWKELIVLSKDAESEDNTLAIDVLIETIEDASILTGDQAGTILKLILQ   400
 401  EGMDGNIFDNKKKLKSNIRAIGMRFAKQFDAIHAELKAKDKKTLKNVLKE   450
 451  YQIEDIVQFASEAVAATQSEESIEIISEEAPSSKKIKLTASEKAQKLAQS   500
 501  SEFAKREVFSGDPINKATEWLNGEKWDKVEWALNEMAQRGEKYFSRKVED   550
 551  DVEQFVLEIVKVVGVGGVKQIDGGSVKAALAGANLNPQFVADLLTKFDGV   600
 601  SEIAPKRTKGAQKKNLVEKTFGTEESWEAFNQRVVFVLDLLNARQIIPSS   650
 651  EKVLAALFAVVKQVNSKSDVESSSYQQHLAVNAIRKILEHPEKTKIGASE   700
 701  VDMDCVIETMRSTHNHHLLRDCLRLIVAAAKHTPNSVVKHVMSVFTFMGN   750
 751  GMLRKDNELTLSIVEKTVESLFSTIINSSGQAVLTKQQQTEKLIELARLF   800
 801  AASAIDIPAHRRARIAQAIARAVQAENASTVVLVLVSSFCARWQRSSDAA   850
 851  AQEAMKRGSDQDAYDDLAIELLSALNPFEQLSSVLEMCEYVRRLGGDKPA   900
 901  KSTTTKKDLDTMIFDRTAQTLPRIRHFRYVVVTLISRIFSNRVLIERLAA   950
 951  YDDEELLKNALPLGKRLIECSVELDEFANKEANDQDGSDPQAQRYWVAFA  1000
1001  SRTEVVSEKLRHLLPGGVAARLIADVLQECVNDKKMSYKMCEKVLQLANI  1050
1051  KLGHDRYLFADSGINEKELITLAQALNKFIVAETKSEEKMRMCQNSAYTL  1100
1101  KLIAKNLPSQSESLVLADTMQRCVSIVSQYQKLDENLTGNVLLLAGELIR  1150
1151  SHNMRSTIHHATSLLKTCLATVQECIARFSKPQYDSAASPGSSVAGGRGN  1200
1201  RGHRIRQQSLGGNKFGSDTLLICSLTCIQRVYDQFASFVVESTGDVIIRY  1250
1251  CRLIARFGDPSELLALNQPSSSTTAAFQGGSQTSGFGSKTGIHHRLSLIR  1300
1301  RSLLSIELRVLPAHIVKTVGELKTEKKALSALFNLLTGYIETQHQQKPEI  1350
1351  LRKSVIQLRRTFVSDVITPTLIVRSQERQSDQFENVEKLEHTVFNFVISI  1400
1401  ASILSEVEFRTVVNELVAWAEPGLEAKADLAARLRLVSLLHFANDLYTSF  1450
1451  NSLALPYFGRILEISALVLKKCNATLLLGTDELLLSGKRGSIEALETDLA  1500
1501  LTLAIDVISNAARHRDFFTVDRCQLVSDVIVNELVNTKVEGHEKRCSDHL  1550
1551  VPAIYRIGNADPDSFPELLNKIMLKTRDSRAKIRYRALIVLELLIKEIGD  1600
1601  GVQPHLSILLPFLNELIEDENKQVEAQCQKVINSLQHKFGETFWSGGSSA  1650

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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