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

NucPred

Fetching P22137 from www.uniprot.org...

The NucPred score for your sequence is 0.23 (see score help below)

   1  MSDLPIEFTELVDLMSLGISPQFLDFRSTTFESDHFVTVRETKDGTNSVA    50
  51  IVDLAKGNEVTRKNMGGDSAIMHPSQMVISVRANGTIVQIFNLETKSKLK   100
 101  SFTLDEPVIFWRWLSETTLGFVTARSILTSNVFDGNVNAKPQLLTLRHAN   150
 151  LNNTQIINFVANKNLDWFAVVGILQENGRIAGRIQLFSKQRNISQAIDGH   200
 201  VAIFTNILLEGNGSTPVQVFVTGNRNATTGAGELRIIEIDHDASLPSQYQ   250
 251  KETTDIFFPPDATNDFPIAVQVSEKYGIIYLLTKYGFIHLYELETGTNLF   300
 301  VNRITAESVFTAAPYNHENGIACINKKGQVLAVEISTSQIVPYILNKLSN   350
 351  VALALIVATRGGLPGADDLFQKQFESLLLQNDYQNAAKVAASSTSLRNQN   400
 401  TINRLKNIQAPPGAISPILLYFSTLLDKGKLNKEETIELARPVLQQDRKQ   450
 451  LFEKWLKEDKLECSEELGDIVKPFDTTLALACYLRAGAHAKVISCLAELQ   500
 501  QFEKIIPYCQKVGYQPNFLVLISSLIRSSPDRASEFAVSLLQNPETASQI   550
 551  DIEKIADLFFSQNHIQQGTSLLLDALKGDTPDQGHLQTRVLEVNLLHAPQ   600
 601  VADAILGNNIFSHYDKPTIASLSEKAGLYQRALENYTDIKDIKRCVVHTN   650
 651  ALPIDWLVGYFGKLNVEQSLACLKALMDNNIQANIQTVVQVATKFSDLIG   700
 701  PSTLIKLFEDYNATEGLYYYLASLVNLTEDKDVVYKYIEAAAKMKQYREI   750
 751  ERIVKDNNVYDPERVKNFLKDANLEDQLPLVIVCDRFDFVHEMILYLYKS   800
 801  QNLKFIETYVQQVNPSKTAQVVGALLDMDCDEAFIQSLLQSVLGQVPINE   850
 851  LTTEVEKRNRLKILLPFLEQSLSQGIQDQAVYNALAKIYIDSNNSPEKFL   900
 901  KENDQYDTLDVGHYCEKRDPYLAYIAYEKGQNDDDLIRITNENSMYKYQA   950
 951  RYLLERSDLDLWNKVLNQENIHRRQLIDSVISVGIPELTDPEPVSLTVQA  1000
1001  FMTNGLKLELIELLEKIILEPSPFNENVALQGLLLLSAIKYEPTKVSSYI  1050
1051  EKLDNYDADEIAPLCIEHDLKEEAFEIYDKHEMYGKALKVLIEDIMSLDR  1100
1101  AASYADKINTPELWSQIGTAQLDGLRIPDAIESYIKAEDPSNYENVIDIA  1150
1151  EQAGKYEELIPFLLMARKTLKEPKIDGALILAYAELNKIHEIENLLAGSN  1200
1201  VANLDHVGDKLFENKEYKAARLCYSAVSNYSKLASTLVYLGDYQAAVDTA  1250
1251  RKASNIKVWKLVNDACIEKKEFKLAQICGLNLIVHAEELDELVERYESNG  1300
1301  YFEELISLFEAGLGLERAHMGMFTELAILYSKYEPDKTFEHLKLFWSRIN  1350
1351  IPKVIRAVEQAHLWSELVFLYAHYDEWDNAALTLIEKSTKDLDHAYFKEV  1400
1401  VVKVSNLEIYYKAINFYVKFHPSLLVDLLTSLTPRLDIPRTVKIFSKSDN  1450
1451  LPLIKPFLINVLPKNNSVVNQAYHDLMIEEEDYKALQDAVDSYDKFDQLG  1500
1501  LASRLESHKLIFFKKIGALLYRRNKKWAKSLSILKEEKLWKDAIETAAIS  1550
1551  QDPKVVEALLTYFVETGNREGFVALLYAAYNLVRIEFVLEISWMNSLEDY  1600
1601  IKPFEISIKKEQNDSIKKITEELAKKSGSNEEHKDGQPLMLMNSAMNVQP  1650
1651  TGF                                                 1653

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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