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

NucPred

Fetching O14522 from www.uniprot.org...

The NucPred score for your sequence is 0.52 (see score help below)

   1  MASLAALALSLLLRLQLPPLPGARAQSAAGGCSFDEHYSNCGYSVALGTN    50
  51  GFTWEQINTWEKPMLDQAVPTGSFMMVNSSGRASGQKAHLLLPTLKENDT   100
 101  HCIDFHYYFSSRDRSSPGALNVYVKVNGGPQGNPVWNVSGVVTEGWVKAE   150
 151  LAISTFWPHFYQVIFESVSLKGHPGYIAVDEVRVLAHPCRKAPHFLRLQN   200
 201  VEVNVGQNATFQCIAGGKWSQHDKLWLQQWNGRDTALMVTRVVNHRRFSA   250
 251  TVSVADTAQRSVSKYRCVIRSDGGSGVSNYAELIVKEPPTPIAPPELLAV   300
 301  GATYLWIKPNANSIIGDGPIILKEVEYRTTTGTWAETHIVDSPNYKLWHL   350
 351  DPDVEYEIRVLLTRPGEGGTGPPGPPLTTRTKCADPVHGPQNVEIVDIRA   400
 401  RQLTLQWEPFGYAVTRCHSYNLTVQYQYVFNQQQYEAEEVIQTSSHYTLR   450
 451  GLRPFMTIRLRLLLSNPEGRMESEELVVQTEEDVPGAVPLESIQGGPFEE   500
 501  KIYIQWKPPNETNGVITLYEINYKAVGSLDPSADLSSQRGKVFKLRNETH   550
 551  HLFVGLYPGTTYSFTIKASTAKGFGPPVTTRIATKISAPSMPEYDTDTPL   600
 601  NETDTTITVMLKPAQSRGAPVSVYQLVVKEERLQKSRRAADIIECFSVPV   650
 651  SYRNASSLDSLHYFAAELKPANLPVTQPFTVGDNKTYNGYWNPPLSPLKS   700
 701  YSIYFQALSKANGETKINCVRLATKGASTQNSNTVEPEKQVDNTVKMAGV   750
 751  IAGLLMFIIILLGVMLTIKRRRNAYSYSYYLKLAKKQKETQSGAQREMGP   800
 801  VASADKPTTKLSASRNDEGFSSSSQDVNGFTDGSRGELSQPTLTIQTHPY   850
 851  RTCDPVEMSYPRDQFQPAIRVADLLQHITQMKRGQGYGFKEEYEALPEGQ   900
 901  TASWDTAKEDENRNKNRYGNIISYDHSRVRLLVLDGDPHSDYINANYIDG   950
 951  YHRPRHYIATQGPMQETVKDFWRMIWQENSASIVMVTNLVEVGRVKCVRY  1000
1001  WPDDTEVYGDIKVTLIETEPLAEYVIRTFTVQKKGYHEIRELRLFHFTSW  1050
1051  PDHGVPCYATGLLGFVRQVKFLNPPEAGPIVVHCSAGAGRTGCFIAIDTM  1100
1101  LDMAENEGVVDIFNCVRELRAQRVNLVQTEEQYVFVHDAILEACLCGNTA  1150
1151  IPVCEFRSLYYNISRLDPQTNSSQIKDEFQTLNIVTPRVRPEDCSIGLLP  1200
1201  RNHDKNRSMDVLPLDRCLPFLISVDGESSNYINAALMDSHKQPAAFVVTQ  1250
1251  HPLPNTVADFWRLVFDYNCSSVVMLNEMDTAQFCMQYWPEKTSGCYGPIQ  1300
1301  VEFVSADIDEDIIHRIFRICNMARPQDGYRIVQHLQYIGWPAYRDTPPSK  1350
1351  RSLLKVVRRLEKWQEQYDGREGRTVVHCLNGGGRSGTFCAICSVCEMIQQ  1400
1401  QNIIDVFHIVKTLRNNKSNMVETLEQYKFVYEVALEYLSSF           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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