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

NucPred

Fetching Q9SAC6 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MSNSVVHNLLNRGLIRPLNFEHQNKLNSSVYQTSTANPALGKIGRSKLYG    50
  51  KGLKQAGRSLVTETGGRPLSFVPRAVLAMDPQAAEKFSLDGNIDLLVEVT   100
 101  STTVREVNIQIAYTSDTLFLHWGAILDNKENWVLPSRSPDRTQNFKNSAL   150
 151  RTPFVKSGGNSHLKLEIDDPAIHAIEFLIFDESRNKWYKNNGQNFHINLP   200
 201  TERNVKQNVSVPEDLVQIQAYLRWERKGKQMYNPEKEKEEYEAARTELRE   250
 251  EMMRGASVEDLRAKLLKKDNSNESPKSNGTSSSGREEKKKVSKQPERKKN   300
 301  YNTDKIQRKGRDLTKLIYKHVADFVEPESKSSSEPRSLTTLEIYAKAKEE   350
 351  QETTPVFSKKTFKLEGSAILVFVTKLSGKTKIHVATDFKEPVTLHWALSQ   400
 401  KGGEWLDPPSDILPPNSLPVRGAVDTKLTITSTDLPSPVQTFELEIEGDS   450
 451  YKGMPFVLNAGERWIKNNDSDFYVDFAKEEKHVQKDYGDGKGTAKHLLDK   500
 501  IADLESEAQKSFMHRFNIAADLVDEAKSAGQLGFAGILVWMRFMATRQLV   550
 551  WNKNYNVKPREISKAQDRLTDLLQDVYASYPEYRELLRMIMSTVGRGGEG   600
 601  DVGQRIRDEILVIQRKNDCKGGIMEEWHQKLHNNTSPDDVVICQALMDYI   650
 651  KSDFDLSVYWKTLNDNGITKERLLSYDRAIHSEPNFRGEQKDGLLRDLGH   700
 701  YMRTLKAVHSGADLESAIQNCMGYQDDGEGFMVGVQINPVSGLPSGYPDL   750
 751  LRFVLEHVEEKNVEPLLEGLLEARQELRPLLLKSHDRLKDLLFLDLALDS   800
 801  TVRTAIERGYEQLNDAGPEKIMYFISLVLENLALSSDDNEDLIYCLKGWQ   850
 851  FALDMCKSKKDHWALYAKSVLDRSRLALASKAERYLEILQPSAEYLGSCL   900
 901  GVDQSAVSIFTEEIIRAGSAAALSSLVNRLDPVLRKTANLGSWQVISPVE   950
 951  VVGYVIVVDELLTVQNKTYDRPTIIVANRVRGEEEIPDGAVAVLTPDMPD  1000
1001  VLSHVSVRARNGKICFATCFDSGILSDLQGKDGKLLSLQPTSADVVYKEV  1050
1051  NDSELSSPSSDNLEDAPPSISLVKKQFAGRYAISSEEFTSDLVGAKSRNI  1100
1101  GYLKGKVPSWVGIPTSVALPFGVFEKVISEKANQAVNDKLLVLKKTLDEG  1150
1151  DQGALKEIRQTLLGLVAPPELVEELKSTMKSSDMPWPGDEGEQRWEQAWA  1200
1201  AIKKVWASKWNERAYFSTRKVKLDHDYLCMAVLVQEVINADYAFVIHTTN  1250
1251  PSSGDSSEIYAEVVKGLGETLVGAYPGRSLSFICKKNNLDSPLVLGYPSK  1300
1301  PIGLFIRRSIIFRSDSNGEDLEGYAGAGLYDSVPMDEEDQVVLDYTTDPL  1350
1351  ITDLSFQKKVLSDIARAGDAIEKLYGTAQDIEGVIRDGKLYVVQTRPQV   1399

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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