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

NucPred

Fetching Q17307 from www.uniprot.org...

The NucPred score for your sequence is 0.71 (see score help below)

   1  MKLAFNKLLVASVVFTVLSFGLLLASLFTTTATTPSEWTILLPEFRFPVN    50
  51  KKQTTEQFLVEKIVHEHEEGEDVRSALYLTHHGYFMNAIANMKVTYRQKS   100
 101  YTVNDVCFKPHSAIFENVPAPENIDKLPAYFQRLLLEMQRLSPCLIVTPL   150
 151  NCFYDSYHIHSEISNWNASTDYLNRRLRNSYLEAIEEKDSRPYVKSTYGP   200
 201  ELIKEWARHMFAIPSKPLSNFSKSDLYSRVKTWLSSIAARKKICADPMRS   250
 251  CDETLDAENYFNVCTVMQQINDYDERRKQRLKFQLEYGDEEFTTRLDCVE   300
 301  DREKFIEWMQERNLRDMLKLFASSVEIPDHKEIPNQVCDGIYHDLDTSSG   350
 351  LELFRGARSFSNNTSAYDTINVELGFMTPENLLTTMRHSDFVNGFESIWT   400
 401  IERARELLNEFRLALKVEVTKFSESRSSRRVKVTTRIVNQIEEEGSDEEM   450
 451  EYHMIYFILGACALMVALFAAFAFSEAFLTSLSMFLLRGFITGLLFIFLC   500
 501  KSGGLILIDSNFLCYITMHLAFNLVMTARVTFICYRIGGCVQSEKDFVKS   550
 551  NFSSLGSVPVDSLKEDSCKRHVQYVLAKYTKFQVAQDAYSEEPFEKLPKY   600
 601  WFLIAIVLVPVIGVYWFFIDSDVQKICIVLLPAFLIAAFEEMRVKNQLLR   650
 651  ERRIKKAIQRLQKEENTRIMSRGEIDNLLSGNAELSGEKSHYESKQGVLH   700
 701  HGSAGGLFELSRSTYDVSLIMAYPNQMIRNLRLCALGAYFRLFKMKYCAV   750
 751  VVSSVAALLILLSIGLLFIPVQRSSVPKELQQDELSIDFAIPNVSSSSWE   800
 801  SINEYLEEFNSEIDSITNLQTITNGRRVLINSTSKINNFLKWVDDEPISW   850
 851  YLTAPLTRPYRKTHLPNPFRFQFRYGFDSIQKSTIIDVVERIDTLLTKYT   900
 901  ETLSFPKAIGFLYEHYHQKAVVWNSFAYHEIFAAAVLAGFFSIIVVFFSI   950
 951  GPVVLPTLAFAFFVVGNRLEIAAIVSLFSLEYHQCYTNVAVFVGFLAAWT  1000
1001  PFCDLARFRGRLLYKDQTRRTPELATQRRIRVPHVAAVDTVQIFAIFLTA  1050
1051  TILLIVITAIIPQFRAFFIPTVILLITLLLAVFNSLAVSLAAYQMFEHEV  1100
1101  RHCYHDQLQSLTTTGKVCDMTRKKLLPREEDLSIPMEEFSIRPTENTKHY  1150
1151  APRPIDNSDPPEQAADEEVVNQDPSMEAARRQYVEFTHRTTGMPIELINQ  1200
1201  FVDNFPVFNVPANFLPNYFALGGAPLDANNGVLLRQPGIAPPPRPNREED  1250
1251  EEERFGLGGGEDDDSYPSSGDDIGDPAKEQQEVTDDVATRYKEEEVRKKV  1300
1301  QPAVPNYDDPNVPGPSNPVPRQVEQVSREAPEDSPNREPRILVYQRPPRL  1350
1351  HEIPQISHGRNPLHDPPSMEEYVQKYDDPNQPPSRRADQYPPSFTPAMVG  1400
1401  YCEDVYWKYNERNLPDNVPMPPRPRDWDQRRLVELPPPEDFDEVPPPGRS  1450
1451  AIPIPPGAIRLRERRREQHLREQEARRNRPESPDDTPGL             1489

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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