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

NucPred

Fetching Q9NIW4 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MSLRSNKLLVAAVIFTVVTFGLLLTSSIFNNKTTTSLTYGGILPKFGQRI    50
  51  IEKKSNEEYIIEKIEHTQKDGEDVRSTRYLTHHSYLLRNLAKMEVKHHGK   100
 101  DFSINDICYKPHNAIFETTFAPENIDKLPNYLQRLILEAQRLSPCLIVTP   150
 151  LNCYHDSYRIHSEMSKWNTSNVTNFLNRKLRNSYIDAIGESEERPYIKST   200
 201  YGPDLIKEWAHLMFKLPSKQTSSFSKKDLSSKIELWLSSIESKTNLTELG   250
 251  RPSEVDNYFDICTSMQQVHDFDERKRKFGLYDDDDEFLIGLDCVENKTKF   300
 301  IEWIQERELRGVSKPFNPNQQCDGIFKNSEGLEFFYGTRSFGNNTAPFDK   350
 351  MKTEIGLMTPEQILTTMLHSDFVNGFESIWTIERAQELLDDFRLAIRQEV   400
 401  KRFNENRSSLKIGIDTRVVQREESNETELEISSNLDSVVYFILFIRCVLL   450
 451  IFFAFFAWSVNPLRSAVMFLVRDALTSLLFSILCKSDGQIELNSELLGYI   500
 501  ILLTIVNTYLTTRVSWYKDRNETCIQRAKDFPSRSNFSLLFSIDSLRENC   550
 551  DSRQLQYALAKLSKYLTALDTYSTETFMQLPNYWPFISILFVPITGCYWY   600
 601  FVDINLPKISVVLLPSFIVATIEQRQVEKSLLKERKAKKEFQKVQKKKME   650
 651  KFLSDGAVDRLLSGNSESVEDKKLYKSKDCVIHKESAGRLYELSRSSYDV   700
 701  SKIMAYPNQRVRDFRFDALGCYFWLMKLKSAGILLYGSAVLFVLLSVAVM   750
 751  LIPIQRTSLQKDMNNEVYFGFSINNMSSDWANINKNLHAFNSEIDSIQSL   800
 801  QTISNWKKGFDRFEGRFYKNSSRISDANDYVEWMNQEPINWSVMAPLTRI   850
 851  SPKFGIPSPFKFRFRYQIEVNNNESEVIDTVQRIDTLLTKYKGTLSSPIV   900
 901  DGVLYEYYHGNAAVWNSFVFNELLASGILSAFFALIVVIFSITPSISSVL   950
 951  IFSFFVIGSRLEIAAVISLFSLDNQQLYTDSAVLVGFLVAWAPFYELSLF  1000
1001  RRRLLYKLKTRCTPELSSGKRIRPPFTKAVDTAQVFAIVLAASLIIAVVA  1050
1051  GVVPEFQKFFWPTVILIVVQLVAFGNSIAVLVATNQMFEREVRNFLDNEF  1100
1101  ELGNGTTAGQVCHMAQKLIPPKYDIPIPMNDFHIRPTNMSKFYAPPPAKK  1150
1151  RAKQTNNETDPEKKEDEPGTSNANNVSQEEAAHRLAILPWHFVLGGIPVD  1200
1201  LTTRSDQIINGPFIGISSDAMRTHEINSELEDQDDYSSESSVEDVESDPA  1250
1251  PEEEIKYHEENMLHMIEKVQKDAAEKEAKEKVHQVESAQRRAPNFDDPNV  1300
1301  AGPSHRYQRNEERISTDIVPADPPREIPANPVPPPTHVLVQRAPRPHEMP  1350
1351  PVIDRTIPRDPRTEPPNLQECIQQNDDPSLPPHPRRHQYPDHYGRAMISY  1400
1401  CEDVYWTYNDGRLPPNVAMPPRPFDWHYRRVAPPEDFNYVPPPGQPSIPI  1450
1451  PAEAMALREERARAHREQEQRDNSQSPSPSPEPGL                 1485

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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