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

NucPred

Fetching Q9MZF4 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MGFCLALTWTFLVGSWTSMGAQKPISWEVQRFDGWYNNLMEHKWGSKGSR    50
  51  LQRLVPASYADGVYQPLGEPHLPNPRDLSNAAMRGPAGQASLRNRTVLGV   100
 101  FFGYHVLSDLVSVETPGCPAEFLNIRIPPGDPVFDPNGRGDVVLPFQRSR   150
 151  WDPESGQSPSNPRDLTNAVTGWLDGSAIYGSSHSWSDALRSFSGGQLASG   200
 201  PDPAFPRNAQPPLLMWSAPDPASGQRGPGGLYAFGAERGNRDPFLQALGL   250
 251  LWFRYHNLCAQRLARQHPHWGDEELFQHARKRVIATYQNIALYEWLPSFL   300
 301  QQAPVKYAGYNPFLDPSISPEFLVASEQFFSTMVPPGIYMRNASCHFQEV   350
 351  INRNSSISRALRVCNSYWSRKHPNLRRAEDVDALLLGMASQIAEREDHVV   400
 401  VEDVLDFWPGSLKFSRTDHVAGCLQRGRDLGLPSYTKARAALGLPPITRW   450
 451  QDINPALSQNNHTVLEATAALYNQDLSQLELLPGGLLESHGDPGPLFSAI   500
 501  VLNQFVRLRDGDRYWFENTRNGLFSEEEIAEIRNTSLRDVLVAVTNMNPS   550
 551  TLQPNVFFWHMGDPCPQPRQLSTQGLPACAPSTMQDYFEGSGFGFGVTIG   600
 601  TLCCFPLVSLLSAWIVARLRKKNFKKLQGQDRKSVMSEKLVGGMEALEWQ   650
 651  GHKEPCRPVLVHLQPGQICVVDGRLSVLRTIQLRPPQQVNLILSGNRGRR   700
 701  ALLLKIPKEYDLVLLFNLEEERQVLVENLRGALKESGLKFQEWELREQEL   750
 751  MRTAVTRQQRSHLLETFFRHLFSQVLDIDQADAGTLPLDSSQKVQEALTC   800
 801  ELSRAEFAESLGLKPQDMFVESMFSLADKDGNGYLSFREFLDILVVFMKG   850
 851  SPEEKSRLMFRMYDFDGNGLISKDEFIRMLRSFIEISNNCLSKAQLTEVV   900
 901  ESMFRESGFQDKEELTWEDFHFMLRDHDSELRFTQLCVRGVEVPEVIKDL   950
 951  CRRASYISQEKICPSPRVSARCPHSNTEVEWTPQRLQCPVDTDPPQEIRR  1000
1001  RFGKKVTSFQPLLFTEAQREKFQRSRRHQTLQQFKRFIENYRRHIGCVAV  1050
1051  FYAITGGLFLERAYYYAFGAHHMGITDTTRVGIILSRGTAASISFMFSYI  1100
1101  LLTMCRNLITFLRETFLNRYVPFDAAVDFHRLIASTAIVLTVLHSAGHVV  1150
1151  NVYLFSISPLSVLSCLFPGLFHNDGSEFPQKYYWWFFQTVPGLTGVMLLL  1200
1201  VLAIMYVFASHHFRRHSFRGFWLTHHLYILLYVLLIIHGSFGLIQLPRFH  1250
1251  IFFLVPALIYVGDKLVSLSRKKVEISVVKAELLPSGVTHLQFQRPQGFEY  1300
1301  KSGQWVQIACLALGTTEYHPFTLTSAPHEDTLSLHIRAAGPWTTRLREIY  1350
1351  SPPTGDGCAKYPKLYLDGPFGEGHQEWHKFEVSVLVGGGIGVTPFASILK  1400
1401  DLVFKSSVSCQVFCKKIYFIWVTRTQRQFEWLADIIREVEENDCQDLVSV  1450
1451  HIYITQLAEKFDLRTTMLYICERHFQKVLNRSLFTGLRSITHFGRPPFEP  1500
1501  FFKSLQEVHPQVRKIGVFSCGPPGMTKNVEKACQLINRQDRTHFSHHYEN  1550
1551  F                                                   1551

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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