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

NucPred

Fetching P51592 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MVSMQFVLQPLPGSDDQFIERIREVSDKVNRFGYGSHRIFEQLKIPVKEV    50
  51  VIGPAHIGVLLEDGKAFRVSFSINSEKLDLTKSDAKCSTSGGSGTASASK   100
 101  APSSSRPMARSRARLLRATGRSNSTGQGSGSRSTGVIIGGSTSSRPLVTV   150
 151  PATYVPEELISQAEVVLQGKSRNLIIRELQRTNLDVNLAVNNLLSRDDEE   200
 201  AEDTEEGADNYVPEDLISLLDNGFSGDNNSVIIDPSDGLFSEEIFSNYSS   250
 251  IRNLLFDRIRSERSNANANAADSNQSTTRSTSSGTALTGNSGLSAQISVN   300
 301  ADREAFSRWRDRQYYGPRRWISKDDYTWEKDADSKKKEPSPMLSPIWISE   350
 351  ELQPWPEKSSVRFKTIGALYSEFIALSESGDLYQWRWSDAEPYKSETENV   400
 401  YHPKTVSLNIVERVELISANFIRCSVVTETNRVATWMDEQLGYIGAKLEH   450
 451  SCCAFNEFISDSITKIYVCSLYTVVKTESNNIYWWGVLPFDQRRFLWDKF   500
 501  RTKTKKPFKVVATDINVGAQVIMKKCPMYQSGSIGFTCSNGVPKVGQLLN   550
 551  SVWTFTDVCRMKIININTNSGVDKSQAAGNNLNAHGITPDKDLPKSTAMP   600
 601  STGSSKNGQSFSNSKESTDRIDMPPPPSPASSTCSDTGSVTSHKRTKRAT   650
 651  TKEDSNAPQEGRKDEELWEVKDVVFVEDKVGPVGKVLKVDGDFVAVRFPA   700
 701  INAAAVAAAAAATSSTSNTASTSKEEGKEDDWQQCRLLRREDVQIFRTAM   750
 751  STRGPDWLQKQPKKINVGGDAAGAQILTLAVDSRGIHVIKKVLGKIHYSL   800
 801  YNLYNCKQEQNCLFPTDCNSFIGSTPGNILMACNDDCSGNSSTIVLRDGN   850
 851  GALYPLAKDCLGSIKDPQWFDLPPVKSITMSTISLPAMLSGVNLKSKVCM   900
 901  TALLFDTQKLMPHILRCDVKNSFAALGRLEREDQADTALVVEERCDGARN   950
 951  IFHACVIMCAPSSNKDSPPDSPSGGVEKKSLVGLSVARSIPTVSTSAYVS  1000
1001  SIAFGASASSSNENSSFATMSSSAAGSASSTSRDNRTNLRDMMNRLINSD  1050
1051  QAEQSGSQPMATNNEDHAYIPWPAETPAASNLSASSSQNVSDSIEDDISK  1100
1101  IIPSSSQSSMLSNIKLGSPTYTFDLAQRREHALTILQQMCVSPALRPYLC  1150
1151  HMLSTKDAQGQTPFMLSVSCRAYEAGIILLNTILMLSEQDPQLKEAMIFP  1200
1201  NGSPADQSPLHVICYNDTCSFTWTGADHINQNIFECKTCGLTGSLCCCTE  1250
1251  CARVCHKGHDCKLKRTAPTAYCDCWEKCKCKALIAGNLTKRFALLCKLVS  1300
1301  CTDLVTKFNSKGESILLFLIQTVGRQIVEQRQYRFSVRVRNVSTAATGAT  1350
1351  GNNSVISNRKTSAAEIDNDMPDHDLEPPKFARKALERLLIDWNAVRSMIM  1400
1401  SGAERGDVPNPAGSASENSNSEGFNMFIQTQHGSTLLDKFTHSLIVKCTS  1450
1451  DHLDTLLLTLVRELQNASVSNRSKEAEEVVRRFVRSVARVFVIFNLEKQP  1500
1501  NPEKRKSHSSCNKYVQSCVKVFQTLHKISIEELCEVSEALIAPVRLGVVR  1550
1551  PTAPFTMSSSNLDNSDDLFSVDPLAPSNVESPSEQILVHDAGNDQSANFN  1600
1601  IQQNYDVVAMETIRDASESEEVINREANSHNQDDELIENQRNEDGMQDDE  1650
1651  SDNDFTFNDAETESDSDDNQSNQEVQRSVQAGATVGSENDIGVLFLEDES  1700
1701  GDSSAQEEDGSEDGESDDQSDEFNFNEQQLERRSTNSNARSDLAPQTMQW  1750
1751  AIRSRDTARSSVRVPTGSNMVFIDPMALRRSTVPASTTVTTPSIEPHTMA  1800
1801  TTASNLARAFGITIRQISELISILSYNVLNDIETSLKIQNDEAIAVQAFV  1850
1851  EKRLKATWDWMFTVMDGTEAQLKFGAYLTNYTDPNHPLHPLNLSAQASSS  1900
1901  QTPAPATSSSVNGVNIMGSNSRRDFFTYCLSLMRSHTSEHRDALPVLDIT  1950
1951  ALRHIAYVLDAFVYYMRNDSGFYDKQDTISGRINNLSPMTESYDTDDELA  2000
2001  NLEEFNADVQMSASSMPSGSQGTRRHAFFARSESTLSLGCSAPEGFELPL  2050
2051  DMAMPLADKPHLLQPNSKRQELFANLPLLVTTNANNSGATNDGDGGSIFD  2100
2101  YTPTRLGFSNSLKRNERVYETVPIDSSKTGDGNVTNKAEGSTDSNIYVQL  2150
2151  KKKQGSDDFKSHKEADGNQSKYEKVVLMETDDSLPSTSKSTEALMATRPE  2200
2201  VIIAPNKASVSPATAARSVIVLAGGSCLKTIDSDINNYSASNLSTAEQAK  2250
2251  CDTQYQKSTSDHLLLFPARGSQFYQSNFSELPSWNFLLSRWKLTLDLFGR  2300
2301  VFMDDVGMEHGSVLPELRGFPVKEMRFRRHMEKLRNGQQRDLVLCKLERN  2350
2351  RESLIVQTFKELNTQFGNQSRRIQPPITFNRVKVTFKDEPGEGSGVARSF  2400
2401  YTSIAEALLASAKIPNLESVQVGTNHSKYVVPFSSILRSRTVSGSSRDQS  2450
2451  TLQRRGSNSKILWRSARERKALNLDARPYTPPNSSDNATPESLNDHLSVH  2500
2501  LQQIGERLYPKIHSINQTHAPKITGMLLEIPTPQLLSVISSDETLRQKVN  2550
2551  EAIEIITFKQKSETSAQSSQPKKSPSVVVVDPVDDDNEPLFYSPGKRGFY  2600
2601  TPRQGFASFERINAFRNIGRLIGLCLLQNELLPLFLQRHVLKYILGRKIK  2650
2651  FHDLAFFDPALYESFRQIIQNAQTKEGEETINRMELCFVIDLMKEEGCGN  2700
2701  RELIPGGRDVAVTSSNIFEYVRRYTEYRLIKSQEKALEALKDGVFDVLPD  2750
2751  NSMINLTAEDLRLLLNGVGDINVSTLISYTTFNDESSEGPDKLLKFKKWF  2800
2801  WSIVEKMNIMERQDLVYFWTGSPALPASEEGFQPLPSVTIRPADDSHLPT  2850
2851  ANTCISRLYIPLYSSKSILRSKMLMAIKSKNFGFV                 2885

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.