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

NucPred

Fetching Q9BXM0 from www.uniprot.org...

The NucPred score for your sequence is 0.28 (see score help below)

   1  MEARSRSAEELRRAELVEIIVETEAQTGVSGINVAGGGKEGIFVRELRED    50
  51  SPAARSLSLQEGDQLLSARVFFENFKYEDALRLLQCAEPYKVSFCLKRTV   100
 101  PTGDLALRPGTVSGYEIKGPRAKVAKLNIQSLSPVKKKKMVPGALGVPAD   150
 151  LAPVDVEFSFPKFSRLRRGLKAEAVKGPVPAAPARRRLQLPRLRVREVAE   200
 201  EAQAARLAAAAPPPRKAKVEAEVAAGARFTAPQVELVGPRLPGAEVGVPQ   250
 251  VSAPKAAPSAEAAGGFALHLPTLGLGAPAPPAVEAPAVGIQVPQVELPAL   300
 301  PSLPTLPTLPCLETREGAVSVVVPTLDVAAPTVGVDLALPGAEVEARGEA   350
 351  PEVALKMPRLSFPRFGARAKEVAEAKVAKVSPEARVKGPRLRMPTFGLSL   400
 401  LEPRPAAPEVVESKLKLPTIKMPSLGIGVSGPEVKVPKGPEVKLPKAPEV   450
 451  KLPKVPEAALPEVRLPEVELPKVSEMKLPKVPEMAVPEVRLPEVELPKVS   500
 501  EMKLPKVPEMAVPEVRLPEVQLLKVSEMKLPKVPEMAVPEVRLPEVQLPK   550
 551  VSEMKLPEVSEVAVPEVRLPEVQLPKVPEMKVPEMKLPKVPEMKLPEMKL   600
 601  PEVQLPKVPEMAVPDVHLPEVQLPKVPEMKLPEMKLPEVKLPKVPEMAVP   650
 651  DVHLPEVQLPKVPEMKLPKMPEMAVPEVRLPEVQLPKVSEMKLPKVPEMA   700
 701  VPDVHLPEVQLPKVCEMKVPDMKLPEIKLPKVPEMAVPDVHLPEVQLPKV   750
 751  SEIRLPEMQVPKVPDVHLPKAPEVKLPRAPEVQLKATKAEQAEGMEFGFK   800
 801  MPKMTMPKLGRAESPSRGKPGEAGAEVSGKLVTLPCLQPEVDGEAHVGVP   850
 851  SLTLPSVELDLPGALGLQGQVPAAKMGKGERVEGPEVAAGVREVGFRVPS   900
 901  VEIVTPQLPAVEIEEGRLEMIETKVKPSSKFSLPKFGLSGPKVAKAEAEG   950
 951  AGRATKLKVSKFAISLPKARVGAEAEAKGAGEAGLLPALDLSIPQLSLDA  1000
1001  HLPSGKVEVAGADLKFKGPRFALPKFGVRGRDTEAAELVPGVAELEGKGW  1050
1051  GWDGRVKMPKLKMPSFGLARGKEAEVQGDRASPGEKAESTAVQLKIPEVE  1100
1101  LVTLGAQEEGRAEGAVAVSGMQLSGLKVSTAGQVVTEGHDAGLRMPPLGI  1150
1151  SLPQVELTGFGEAGTPGQQAQSTVPSAEGTAGYRVQVPQVTLSLPGAQVA  1200
1201  GGELLVGEGVFKMPTVTVPQLELDVGLSREAQAGEAATGEGGLRLKLPTL  1250
1251  GARARVGGEGAEEQPPGAERTFCLSLPDVELSPSGGNHAEYQVAEGEGEA  1300
1301  GHKLKVRLPRFGLVRAKEGAEEGEKAKSPKLRLPRVGFSQSEMVTGEGSP  1350
1351  SPEEEEEEEEEGSGEGASGRRGRVRVRLPRVGLAAPSKASRGQEGDAAPK  1400
1401  SPVREKSPKFRFPRVSLSPKARSGSGDQEEGGLRVRLPSVGFSETGAPGP  1450
1451  ARMEGAQAAAV                                         1461

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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