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

NucPred

Fetching Q9DEY9 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MAALPQNNLQKQLELFPAKGTSNKLSLQKTKSSVFTFKKKCSPNVSASTG    50
  51  FIPFQQHVLKDKNVNVKQDGTHTALPKATERNKINCFFTPVYTKSGQPPQ   100
 101  VVALKDHVHGNDSANKPPSTEDAASKKTGINTSFGSVTSLEEWDDLDDFD   150
 151  TSVSPPKSHAGKGGKTPQKCKNTSPVASFKIQSISPEGPTTEKHDCAKLL   200
 201  YDNNEVASEPRKNLHAKTAESPDQSLVCLASVEPTNLERDMCRNTDYLGT   250
 251  DDLEHDQETLSQVLIEEEDDCEPDFIPPSPSDESLSSPPVLKVISAQRKH   300
 301  KVSSLTDVNDCENTTDHLQGQSVSTSLDSKVPSQLLTLMLEICDLVDKIP   350
 351  ISELHVLSCGLDLKKKRDMRKRLLSNDSVFRSSPADSSTVSLTSCTSSTQ   400
 401  NRDFNVNAPKGAESLSGSSVSKVFKFNKLAVHDIGTKESENSANSAPNFM   450
 451  EKIGNKTSFSFRAGGDSIMENSFNFHSSVLSNSRFNTPQNEKPISSSTCT   500
 501  RPYSQPIDDMDNPDLDFDIDNFDIEDLDDIHCLDSPAAPSVSSKNVPQYP   550
 551  TIREAQLDSRNKEKNTRNNTGDTTNPSLLSDSLLKPQIENPAHERFRGFN   600
 601  FPHSKEMMKIFHKKFGLHRFRTNQLEAINACLCGEDCFILMPTGGGKSLC   650
 651  YQLPGCISPGVTIVISPLRSLIVDQVQKLTSLDIPATYLTGDKTDAEAAS   700
 701  IYLQLSKKDPIIKLLYVTPEKVCASTRLISTMENLYERQLLARFVIDEAH   750
 751  CVSQWGHDFRPDYKRLNVLRQKFQSVPMMALTATANPRVKKDILNQLKMT   800
 801  KPQIFTMSFNRDNLKYEVLPKKPKRVALDCVEWIKKHHPNDSGIIYCLSR   850
 851  HECDTMADTLQKEGLAALAYHAGLADSNRDYVQHKWINQDDCQVICATIA   900
 901  FGMGIDKPDVRYVIHASLPKSVEGYYQESGRAGRDGETSHCLLFYSYHDV   950
 951  TRIRRLIQMEKDGNSHTKQTHFNNLYSMVHYCENVVECRRMQLLSYFGEN  1000
1001  NFNPNFCKEHTQVACDNCLGKKNYKSRDVTDDVGNIVRFVQDNCSLVQGR  1050
1051  GKGRSNNTRLTLNMMVDIFLGSKSAKIQTGLFGKGAAYSRHNAERLFRKL  1100
1101  VLDRIIDEELYITFNDQAVAYVKMGERAQAVLNGFLKVDFQDTESASSIR  1150
1151  KQKASVVTNTSQREEMVKKCQAELTELCKRLGKIFGVHYFNIFNTATIRR  1200
1201  IAESLSPEPEVLLQIDGVTEDKLDKYGAELIDVLQKYSEWTLPVEDICQK  1250
1251  SGGPANVSARRSNSDHDDESCDKSSYFSSNNKKGPKRKNSSYFGKSKKRK  1300
1301  TGGDGQQSRSKNGNSSYARKNSTAKTSSSYISGSKTGADKRPGFMAPPMP  1350
1351  QPNRRFLKPSYSMF                                      1364

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.)

Go back to the NucPred Home Page.