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

NucPred

Fetching P25558 from www.uniprot.org...

The NucPred score for your sequence is 0.87 (see score help below)

   1  MEKDLSSLYSEKKDKENDETLFNIKLSKSVVETTPLNGHSLFDDDKSLSD    50
  51  WTDNVFTQSVFYHGSDDLIWGKFFVCVYKSPNSNKLNAIIFDKLGTSCFE   100
 101  SVDISSNSQYYPAIENLSPSDQESNVKKCIAVILLQRYPLLSPSDLSQIL   150
 151  SNKSENCDYDPPYAGDLASSCQLITAVPPEDLGKRFFTSGLLQNRFVSST   200
 201  LLDVIYENNESTIELNNRLVFHLGEQLEQLFNPVTEYSPEQTEYGYKAPE   250
 251  DELPTESDDDLVKAICNELLQLQTNFTFNLVEFLQKFLIALRVRVLNEEI   300
 301  NGLSTTKLNRLFPPTIDEVTRINCIFLDSLKTAIPYGSLEVLKACSITIP   350
 351  YFYKAYTRHEAATKNFSKDIKLFIRHFSNVIPEREVYTEMKIESIIKGPQ   400
 401  EKLLKLKLIIERLWKSKKWRPKNQEMAKKCYNNIIDVIDSFGKLDSPLHS   450
 451  YSTRVFTPSGKILTELAKCWPVELQYKWLKRRVVGVYDVVDLNDENKRNL   500
 501  LVIFSDYVVFINILEAESYYTSDGSNRPLISDILMNSLINEVPLPSKIPK   550
 551  LKVERHCYIDEVLVSILDKSTLRFDRLKGKDSFSMVCKLSSAFISSSSVA   600
 601  DLITKARILEKDTAFHLFKASRSHFTLYSTAHELCAYDSEKIKSKFALFL   650
 651  NIPPSKEILEVNNLHLAFFARFCSNDGRDNIVILDVLTKHDDKHIEVTSD   700
 701  NIVFTIINQLAIEIPICFSSLNSSMAKDLLCVNENLIKNLEHQLEEVKHP   750
 751  STDEHRAVNSKLSGASDFDATHEKKRSYGTITTFRSYTSDLKDSPSGDNS   800
 801  NVTKETKEILPVKPTKKSSKKPREIQKKTKTNASKAEHIEKKKPNKGKGF   850
 851  FGVLKNVFGSKSKSKPSPVQRVPKKISQRHPKSPVKKPMTSEKKSSPKRA   900
 901  VVSSPKIKKKSTSFSTKESQTAKSSLRAVEFKSDDLIGKPPDVGNGAHPQ   950
 951  ENTRISSVVRDTKYVSYNPSQPVTENTSNEKNVEPKADQSTKQDNISNFA  1000
1001  DVEVSASSYPEKLDAETDDQIIGKATNSSSVHGNKELPDLAEVTTANRVS  1050
1051  TTSAGDQRIDTQSEFLRAADVENLSDDDEHRQNESRVFNDDLFGDFIPKH  1100
1101  YRNKQENINSSSNLFPEGKVPQEKGVSNENTNISLKTNEDASTLTQKLSP  1150
1151  QASKVLTENSNELKDTNNEGKDAKDIKLGDDYSDKETAKEITKPKNFVEG  1200
1201  ITERKEIFPTIPRLAPPASKINFQRSPSYIELFQGMRVVLDKHDAHYNWK  1250
1251  RLASQVSLSEGLKVNTEEDAAIINKSQDDAKAERMTQISEVIEYEMQQPI  1300
1301  PTYLPKAHLDDSGIEKSDDKFFEIEEELKEELKGSKTGNEDVGNNNPSNS  1350
1351  IPKIEKPPAFKVIRTSPVRIIGRTFEDTRKYENGSPSDISFTYDTHNNDE  1400
1401  PDKRLMELKFPSQDEIPDDRFYTPAEEPTAEFPVEELPNTPRSINVTTSN  1450
1451  NKSTDDKLSSGNIDQKPTELLDDLEFSSFNIAFGNTSMSTDNMKISSDLS  1500
1501  SNKTVLGNAQKVQESPSGPLIYVLPQSSTKHEKEGFLRKKQKDEPIWVSP  1550
1551  SKIDFADLSRRTKALTPERNTVPLKNNDSRKYKYTGEGSIGNMTNMLLTK  1600
1601  DASYAYLKDFVALSDDEDEDGKQNCAVGGPEKLKFY                1636

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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