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

NucPred

Fetching Q23670 from www.uniprot.org...

The NucPred score for your sequence is 0.69 (see score help below)

   1  MSDSDSEFSIEDSPKKKTAPKKEKASPKKKKDDANESMVMTEEDRNVFTS    50
  51  IDKKGGGSKQMAIEDIYQKKSQLEHILLRPDTYIGSVEHTEKTPMWVYNM   100
 101  EESKLEQRDISYVPGLYKIYDEILVNAADNKQRDPKMNTIKITINKEKNE   150
 151  ISVYNNGKGIPVTQHKVEKVYVPELIFGTLLTSSNYNDDEKKVTGGRNGY   200
 201  GAKLCNIFSTKFTLETSSRDYKSAFKQTWIKNMTRDEEPKIVKSTDEDFT   250
 251  KITFSPDLAKFKMKELDDDICHLMARRAYDVAGSSKGVAVFLNGKRIPIK   300
 301  GFEDYVQMYTSQFNNEGEPLKIAYEQVGDRWQVALALSEKGFQQVSFVNS   350
 351  IATTKGGRHVDYVADQMVAKFIDSIKRKLTKTSMNIKPFQIKNHMWVFVN   400
 401  CLIENPTFDSQTKETMTLQQKQFGSTCVLSEKFSKAASSVGITDAVMSWV   450
 451  RFKQMDDLNKKCSKTKTSKLKGIPKLEDANDAGTKNSQQCTLILTEGDSA   500
 501  KTLAVSGLSVVGRDKYGVFPLRGKLLNVREGNMKQIADNAEVNAMIKILG   550
 551  LQYKKKYETEDDFKTLRYGKLMVMADQDQDGSHIKGLVINFIHHFWPSLI   600
 601  QRNFVEEFITPIVKATKGKEEVSFYSLPEYSEWRMNTDNWKSYKIKYYKG   650
 651  LGTSTSKEAKEYFLDMVRHRIRFKYNGADDDNAVDMAFSKKKIEERKDWL   700
 701  SKWMREKKDRKQQGLAEEYLYNKDTRFVTFKDFVNRELVLFSNLDNERSI   750
 751  PCLVDGFKPGQRKVLFACFKRADKREVKVAQLAGAVAEISAYHHGEQSLM   800
 801  GTIVNLAQDYVGSNNINLLLPIGQFGTRLQGGKDSASARYIFTQLSPVTR   850
 851  TLFPAHDDNVLRFLYEENQRIEPEWYCPIIPMVLVNGAQGIGTGWSTNIP   900
 901  NYNPRELVKNIKRLIAGEPQKALAPWYKNFRGKIIQIDPSRFACYGEVAV   950
 951  LDDNTIEITELPIKQWTQDYKEKVLEGLMESSDKKSPVIVDYKEYHTDTT  1000
1001  VKFVVKLSPGKLRELERGQDLHQVFKLQAVINTTCMVLFDAAGCLRTYTS  1050
1051  PEAITQEFYDSRQEKYVQRKEYLLGVLQAQSKRLTNQARFILAKINNEIV  1100
1101  LENKKKAAIVDVLIKMKFDADPVKKWKEEQKLKELRESGEIELDEDDLAA  1150
1151  VAVEEDEAISSAAKAVETKLSDYDYLVGMALIKLSEEEKNKLIKESEEKM  1200
1201  AEVRVIEKKTWQDLWHEDLDNFVSELDKQEAREKADQDASIKNAAKKLAA  1250
1251  DAKTGRGPKKNVCTEVLPSKDGQRIEPMLDAATKAKYEKMSQPKKERVKK  1300
1301  EPKEPKEPKKVKKEGQDIKKFMSPAAPKTAKKEKSDGFNSDMSEESDVEF  1350
1351  DEGIDFDSDDDGVEREDVVSKPKPRTGKGAAKAEVIDLSDDDEVPAKKPA  1400
1401  PAKKAAPKKKKSEFSDLSGGDSDEEAEKKPSTSKKPSPKKAAPKTAEPKS  1450
1451  KAVTDFFGASKKNGKKAAGSDDEDDESFVVAPREKSGRARKAPPTYDVDS  1500
1501  GSDSDQPKKKRGRVVDSDSD                                1520

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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