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

NucPred

Fetching Q9US25 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MEPEHSNYDLKNHPTSVQESTLNGSAVTDPQFGNTTNSLPSMNGLLNHEN    50
  51  SFASQQSLSSSAFDDSEIVTSTANSTVVSSALSTPKIDDAQNSDDVRVDG   100
 101  TRRSSRAKRPVYRDFSYTEIDEHEIPIPKKRKSKPAPKQKKSVASDDEDA   150
 151  YDKRHRFSINSASGTEIRTSLRSSKGKSVNYNEQEFYDDFEDEEEEVEEQ   200
 201  VEEEYEPIIDFVLNHRKRADAQDDDPKSSYQYLIKWQEVSHLHNTWEDYS   250
 251  TLSSVRGYKKVDNYIKQNIIYDREIREDPTTTFEDIEALDIERERKNMLF   300
 301  EEYKIVERIVASETNEEGKTEYFVKWRQLPYDNCTWEDADVIYSMAPNEV   350
 351  YQFLQRENSPYLPYKGVFYNTRPPYRKLEKQPSYIKGGEIRDFQLTGINW   400
 401  MAYLWHRNENGILADEMGLGKTVQTVCFLSYLVHSLKQHGPFLIVVPLST   450
 451  VPAWQETLANWTPDLNSICYTGNTESRANIREYEFYLSTNSRKLKFNILL   500
 501  TTYEYILKDKQELNNIRWQYLAIDEAHRLKNSESSLYETLSQFRTANRLL   550
 551  ITGTPLQNNLKELASLVNFLMPGKFYIRDELNFDQPNAEQERDIRDLQER   600
 601  LQPFILRRLKKDVEKSLPSKSERILRVELSDMQTEWYKNILTKNYRALTG   650
 651  HTDGRGQLSLLNIVVELKKVSNHPYLFPGAAEKWMMGRKMTREDTLRGII   700
 701  MNSGKMVLLDKLLQRLKHDGHRVLIFSQMVRMLNILGEYMSLRGYNYQRL   750
 751  DGTIPASVRRVSIDHFNAPDSPDFVFLLSTRAGGLGINLNTADTVIIFDS   800
 801  DWNPQADLQAMARAHRIGQKNHVNVYRFLSKDTVEEDILERARRKMILEY   850
 851  AIISLGVTEKSKNSKNDKYDAQELSAILKFGASNMFKATENQKKLENMNL   900
 901  DDILSHAEDRDSSNDVGGASMGGEEFLKQFEVTDYKAEDLNWDDIIPEEE   950
 951  MERIEEEERMLAAQRAKEEERERREEEERENDEDHPSRTYKRTTKSITKR  1000
1001  QQRREEMVREKEIRLLYRAMIKFGLVDERFDTIVKEAELQATDPKRIYSL  1050
1051  SADMVKACDEAVERLGADDTKNKQPRKAILIEFKGVKNINAETVTLRVKD  1100
1101  LTHLHRAYKGLDPLKQIIGYPIRSVHSWNCSWGIKEDSMLLAGINKHGFG  1150
1151  CWQAIKNDPDLGLHDKIFLDEAKNDKESRYVPSAVHLVRRGEYLLSVVRE  1200
1201  HPDLFVVKTDQPTKRKYNRKAPTKSSTRQTTLDGSISNTKKSSRTKKKKE  1250
1251  EETNRGDETSPEGTVGEDEVEEEPRQAEPPKRALRSNSGKAASNKRTTRN  1300
1301  SMKTHSAMDTLTAVAALDAELDNMSNEKAKEEVDHVKSENGESVNEPNTE  1350
1351  DLSLETEENTTVSDISPLVKNEA                             1373

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.