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

NucPred

Fetching Q03018 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MMVKQEEPLNEISPNTPMTSKSYLLNDTLSKVHHSGQTRPLTSVLSGDAS    50
  51  SNSIGILAMHNNIIRDFTKIASNNIDLAIEDITTVDHSLNSIYSLLKSHH   100
 101  MWGHINSTVKQHLMIIVKLINNNALGLASSEIIFLFNETNLFQAHSLKNI   150
 151  LLADFSTWNDYYLSNLKILALQIILKRKLVDEYLPHILELFSHDKRYLLK   200
 201  DPNLKAHALTKIVLSFFSVTTSCKVLFGLKFLQYIKQFKLPFKKFISNIT   250
 251  VECFSKNLLHKNYLEMGPNKIYLNSFYLSYSMLYDGLDKIMLLDILSYEE   300
 301  TTEVQRAIKSKKEFNEYCNMSENRLLWSCISVDDLNVILENATNFLQNKG   350
 351  KHISATLKCLVCLWSTIRLEGLPKNKDILRQFDCTVIYINSNIKSINDES   400
 401  AAALLSELLGVLSEICIDYKEPKRLSNIISVLFNASVLFKSHSFLLKTAN   450
 451  LEISNVLISNDSKTSHRTILKFEKFISSAQSAQKKIEIFSCLFNVYCMLR   500
 501  NDTLSFVFDFCQNAFIHCFTRLKITKFIEFSNSSEIMLSVLYGNSSIENI   550
 551  PSENWSQLSRMIFCSLRGIFDLDPLELNNTFDKLHLLNKYELLIRIVYLL   600
 601  NLDMSKHLTTNLSKITKLYINKWLQKSDEKAERISSFEMDFVKMLLCYLN   650
 651  FNNFDKLSIELSLCIKSKEKYYSSIVPYADNYLLEAYLSLYMIDDALMMK   700
 701  NQLQKTMNLSTAKIEQALLHASSLINVHLWDSDLTAFQIYFGKTLPAMKP   750
 751  ELFDINNDHNLPMSLYIKVILLNIKIFNESAKLNIKAGNVISAVIDCRKA   800
 801  QNLALSLLKKKNKLSQGSRLALLKSLSFSFFQLIKIHIRIGSARDCEFYS   850
 851  KELSRIISDLEEPIIVYRCLHFLHRYYMITEQTCLQNITLGKANKAFDYL   900
 901  DAEADITSLTMFLYDNKEFVKLEQSLVLYFGDQLEKTFLPNLWKLHLGKD   950
 951  IDDSICLSEYMPKNVINRVHNMWQKVMSQLEEDPFFKGMFESTLGIPSSL  1000
1001  PVIPSTMPNNILKTPSKHSTGLKLCDSPRSSSMTPRGKNIRQKFDRIAAI  1050
1051  SKLKQMKELLESLKLDTLDNHELSKISSLSSLTLTILSNITSIHNAESSL  1100
1101  ITNFSLTDLPRHMPLLFDKVLNNIDNKNYREFRVSSLIAPNNISTITESI  1150
1151  RVSAAQKDLMESNLNINVITIDFCPITGNLLLSKLEPRRKRRTHLRLPLI  1200
1201  RSNSRDLDEVHLSFPEATKKLLSIINESNQTTSVEVTNKIKTREERKSWW  1250
1251  TTRYDLDKRMQQLLNNIENSWFNGVQGFFSPEVVDNSLFEKFKDKFYEIL  1300
1301  HQNLPSRKLYGNPAMFIKVEDWVIELFLKLNPQEIDFLSKMEDLIYFVLD  1350
1351  ILLFHGEENAYDEIDFSMLHVQLEEQIKKYRATMTTNSIFHTFLVVSSSC  1400
1401  HLFPWECLSFLKDLSITRVPSYVCLNKLLSRFHYQLPLQVTIEDNISMIL  1450
1451  NPNGDLSRTESKFKGMFQKIIDAKPSSQLVMNEKPEEETLLKMLQNSNLF  1500
1501  VYIGHGGGEQYVRSKEIKKCTKIAPSFLLGCSSAAMKYYGKLEPTGTIYT  1550
1551  YLLGGCPMVLGNLWDVTDKDIDKFSEELFEKMGFRCNTDDLNGNSLSVSY  1600
1601  AVSKSRGVCHLRYLNGAAPVIYGLPIKFVS                      1630

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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