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

NucPred

Fetching Q96T23 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MATAAAAAAVMAPPGCPGSCPNFAVVCSFLERYGPLLDLPELPFPELERV    50
  51  LQAPPPDVGNGEVPKELVELHLKLMRKIGKSVTADRWEKYLIKICQEFNS   100
 101  TWAWEMEKKGYLEMSVECKLALLKYLCECQFDDNLKFKNIINEEDADTMR   150
 151  LQPIGRDKDGLMYWYQLDQDHNVRMYIEEQDDQDGSSWKCIVRNRNELAE   200
 201  TLALLKAQIDPVLLKNSSQQDNSSRESPSLEDEETKKEEETPKQEEQKES   250
 251  EKMKSEEQPMDLENRSTANVLEETTVKKEKEDEKELVKLPVIVKLEKPLP   300
 301  ENEEKKIIKEESDSFKENVKPIKVEVKECRADPKDTKSSMEKPVAQEPER   350
 351  IEFGGNIKSSHEITEKSTEETEKLKNDQQAKIPLKKREIKLSDDFDSPVK   400
 401  GPLCKSVTPTKEFLKDEIKQEEETCKRISTITALGHEGKQLVNGEVSDER   450
 451  VAPNFKTEPIETKFYETKEESYSPSKDRNIITEGNGTESLNSVITSMKTG   500
 501  ELEKETAPLRKDADSSISVLEIHSQKAQIEEPDPPEMETSLDSSEMAKDL   550
 551  SSKTALSSTESCTMKGEEKSPKTKKDKRPPILECLEKLEKSKKTFLDKDA   600
 601  QRLSPIPEEVPKSTLESEKPGSPEAAETSPPSNIIDHCEKLASEKEVVEC   650
 651  QSTSTVGGQSVKKVDLETLKEDSEFTKVEMDNLDNAQTSGIEEPSETKGS   700
 701  MQKSKFKYKLVPEEETTASENTEITSERQKEGIKLTIRISSRKKKPDSPP   750
 751  KVLEPENKQEKTEKEEEKTNVGRTLRRSPRISRPTAKVAEIRDQKADKKR   800
 801  GEGEDEVEEESTALQKTDKKEILKKSEKDTNSKVSKVKPKGKVRWTGSRT   850
 851  RGRWKYSSNDESEGSGSEKSSAASEEEEEKESEEAILADDDEPCKKCGLP   900
 901  NHPELILLCDSCDSGYHTACLRPPLMIIPDGEWFCPPCQHKLLCEKLEEQ   950
 951  LQDLDVALKKKERAERRKERLVYVGISIENIIPPQEPDFSEDQEEKKKDS  1000
1001  KKSKANLLERRSTRTRKCISYRFDEFDEAIDEAIEDDIKEADGGGVGRGK  1050
1051  DISTITGHRGKDISTILDEERKENKRPQRAAAARRKKRRRLNDLDSDSNL  1100
1101  DEEESEDEFKISDGSQDEFVVSDENPDESEEDPPSNDDSDTDFCSRRLRR  1150
1151  HPSRPMRQSRRLRRKTPKKKYSDDDEEEESEENSRDSESDFSDDFSDDFV  1200
1201  ETRRRRSRRNQKRQINYKEDSESDGSQKSLRRGKEIRRVHKRRLSSSESE  1250
1251  ESYLSKNSEDDELAKESKRSVRKRGRSTDEYSEADEEEEEEEGKPSRKRL  1300
1301  HRIETDEEESCDNAHGDANQPARDSQPRVLPSEQESTKKPYRIESDEEED  1350
1351  FENVGKVGSPLDYSLVDLPSTNGQSPGKAIENLIGKPTEKSQTPKDNSTA  1400
1401  SASLASNGTSGGQEAGAPEEEEDELLRVTDLVDYVCNSEQL           1441

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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