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

NucPred

Fetching O16140 from www.uniprot.org...

The NucPred score for your sequence is 0.76 (see score help below)

   1  MADIKSMFNKMSSPKQNGTGEPAPAKGQKGAIEKIYQKKSQLEHILLRPD    50
  51  TYIGSVERATETMWVYDKVKECMMQKELTSVPDCSFPGLYKIYDEILVNA   100
 101  ADNKQRDPKMDVIKIDINQETNTISVYNNGSGIPVVMHKDEKMYVPTMIF   150
 151  GHLLTSSNYNDEEEKVTGGRNGYGAKLCNIFSTKFTVETASKQYKKHFKQ   200
 201  TWGSNMTKASEPKIKDSGKDDDFTKIVFSPDLAKFKMEKLEDDIVLLMSR   250
 251  RAYDVAASSQGVKVYLNGERLKINKFKDYVDLYIKGKDDENGQPLKVVYE   300
 301  KVSDRWEVALTISDMGFQQVSFVNSIATTKGGKHVDTVADSVVKNVLEVL   350
 351  KKKNKGGVNIKPYQVKTHMWLFVNCLIVNPTFDSQTKENMTLQAKSFGSK   400
 401  CNLSEKFITAVTKCGLVESVLTWAKFKAQDQLVKASGKKQSKLKGIPKLE   450
 451  DANDAGTKNAHLCTLILTEGDSAKTLAVSGLSVVGRDHYGVFPLEGKPLN   500
 501  VRDASHKQVLENVEINNLIKILGLQYKKKYNSVDDLKTLRYGKVMIMADQ   550
 551  DQDGSHIKGLIINFIHHNWPELLKLPFLEEFITPIVKATKKDKEISFYSL   600
 601  PEFEEWKKETENHHTYNIKYYKGLGTSTSKEAKEYFQNMDRHRIRFKYSG   650
 651  PTDDHHIELAFSKKGADQRKEWLTNHMDEVKRRKEIGLSERYLYTKETKT   700
 701  VTYSDFVNLELVLFSNGDNVRSIPSMIDGLKPGQRKVIFTCIKRNDKREV   750
 751  KVAQLAGSVAEHSAYHHGEQSLAMTIVNLAQNYVGSNNINLLEPRGQFGT   800
 801  RLSGGKDSASPRYIFTLMSPLTRLIFHPHDDPLLVHEFEDNQKIEPVYYL   850
 851  PIIPMVLVNGVEGIGTGWSTKIPNYNPRDIAENLRRLLDGEKPKVMHPWY   900
 901  KNFKGNVEGFGDKYVISGEAAILPGDKIEITELPVGTWTHNYKENVLEPM   950
 951  LGTDKVKPLISEYREYNTDTTVRFVVSLLPGKLSEIEAEGIHKVFKLQTT  1000
1001  ISMTCMNAFDYNCCLEKYDKVEEILREFYDLRVKYYVRRKDYLEGQLQAE  1050
1051  ADKLSNQARFILKKCDKGLVIENKKRKAMVEELIKRGYAPDPIADWKKRA  1100
1101  SKIQGLTALEDDDAQESEEEEPEPDPKGKPVDPDKAFQQLKEVKKFNYLL  1150
1151  GMSMWMLTKEKKDELLKQRDQKLTELTTLKNKTAPMLWREDLDAFLIKLD  1200
1201  EVEDKERREELNVNKKTSKAMAGKKNRKSMFDIIPSENGRRVEPKISDDL  1250
1251  IKRIQAAEKAKTRKEIKKEYDPDDPTGISPSSGEKKPKARVKKEKPEKAE  1300
1301  KPDKVDKAEKTDGLKQTKLTFKKEPKKKKMTFSGSSSGEMSASDAEVEVL  1350
1351  VPRERTNARRAATRVQKYKDGSDDSGSDSEPELLDNKIDSDHEAPQTLSI  1400
1401  SDEDDDFNIKKNPAKKPAEMDSDCLFDSLIEDAKKDEPQKTLTKSKSESI  1450
1451  LIRRLNIERQRRCDTSVPPKEKAAPKRKLMNVDKDEKKTKKRPARVMLDQ  1500
1501  DSDDEDSIFDSKKGKKKTAANPKKKAKKKVESDSESDFNISDSSLSD     1547

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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