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

NucPred

Fetching Q96UP3 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MTKEIAVKEASNMLLQEPSTPSSQAVGLSSSPSSSIRKKKVNFSSELENS    50
  51  PGGNRPSFGLPKRGILKTSTPLSSIKQPNFQSFEGNESEKETSLQELQSS   100
 101  FCSGIENLQHVEKSARIETYSKLSSFLKIYTPSLPEDPIFPLLNQLCNFL   150
 151  LSDRCSNNSEGSPDFQLNTQANKLLSILLWHPTISSHIQPETATVFIEQS   200
 201  LNFLEGPKLTKALAAQHLHLLSCQKCPLSIHPLCNRILDVCFNISFPSLV   250
 251  IGQERLAVLTKILSQFPLEFSRRVVDWAPYLLACLVDASRPIREKALLLA   300
 301  LDLSKHLYHDKLVARTILANFRSDIKGTAFVLIMTEQFEKLVIEEDDGVY   350
 351  VAHAWAAIISVLGGARISSWEYFNTWLKIIQLCFNSMNPLTKCAAQTSWI   400
 401  RLIHEFSLSETLTQATKRLTLLCQPISMVLGSRNLPTVKNAAMTTLIALI   450
 451  YACLRPGISDAMLSLLWDSVIVNILEKCALKNEVTIFESSNILLALFNTL   500
 501  SNGVWKDDRLVCRESVEAKELPKLNPVWVRANCSRTIEPVKTLLLLAKPD   550
 551  HTVKTTTPARKQHIRGLSYEQSSSVWSTYIKCLASAGQKEIKRSVETGRA   600
 601  ICCICSSLHKFLYSKSIRKDELYVERVSRFALMVKSAIEAFGINTFVEAS   650
 651  YLVSDNQLVLIDQTKAIDSYDHVPISPLIYLLHSLALLTNGTLFSTVHAA   700
 701  YSSILSSIEEYHLRFGLKLMLLWDCVSPLSDDGTLVLARVLVSHEVSRLT   750
 751  SEALLSELKSRNGNNSVEEGFSEEERSILLKLLSWNVKFCSISDAGSVNN   800
 801  LLQQYFTAIYKFEGCGSVFPFVVDPFTTILDDVLSFEANKVYSFAISLMK   850
 851  VSTFESCTKELPPVTLPENIRQHLDSYNHMVELYNTLLQRLSSSDQVDLQ   900
 901  CRYLHELSEFIKKIPKEFIFHTICKLSKGLIPCFLMNAFPQLEKSTTLQK   950
 951  SCTNFCILILQLLLNSTATASNILESLSPLLTSGLKSISKEVVLAAIKFW  1000
1001  NQVFGKFESEEYPIELQKTISYLSKTYIILLPFQSLCPGGKQANHQSSEK  1050
1051  MSDILKGVDELRSVSKNGPYASSQDKGEKTTEFSGPGKPNNDNYIQIASV  1100
1101  QELDDSSKGKAGKMPASKKNKRQKGDVKKIDETKNEATDMEESLTTPSGK  1150
1151  VNKEVIVDDTSLRDEAIVPDKAIDVADNSNALLKENISSQSNRKADNNGT  1200
1201  PSVNNSFTTANNDECSKENSQIEPEGQTASREGVLSTPRSTRKKRKLGRK  1250
1251  SQSSNVNKEVAISEVSATLENVEVIERHGISEQGQNLDESACVLTNESSL  1300
1301  SQTEIPEEKTENETTAVNGFENSKKRQFSSLLSGSIDTNNESNKVSSVEF  1350
1351  DKSGPQDIIQSMTEATFEIEKNIQDLKSEEVQKLSDLLMRLQRAILSRIA  1400

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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