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

NucPred

Fetching P35187 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MVTKPSHNLRREHKWLKETATLQEDKDFVFQAIQKHIANKRPKTNSPPTT    50
  51  PSKDECGPGTTNFITSIPASGPTNTATKQHEVMQTLSNDTEWLSYTATSN   100
 101  QYADVPMVDIPASTSVVSNPRTPNGSKTHNFNTFRPHMASSLVENDSSRN   150
 151  LGSRNNNKSVIDNSSIGKQLENDIKLEVIRLQGSLIMALKEQSKLLLQKC   200
 201  SIIESTSLSEDAKRLQLSRDIRPQLSNMSIRIDSLEKEIIKAKKDGMSKD   250
 251  QSKGRSQVSSQDDNIISSILPSPLEYNTSSRNSNLTSTTATTVTKALAIT   300
 301  GAKQNITNNTGKNSNNDSNNDDLIQVLDDEDDIDCDPPVILKEGAPHSPA   350
 351  FPHLHMTSEEQDELTRRRNMRSREPVNYRIPDRDDPFDYVMGKSLRDDYP   400
 401  DVEREEDELTMEAEDDAHSSYMTTRDEEKEENELLNQSDFDFVVNDDLDP   450
 451  TQDTDYHDNMDVSANIQESSQEGDTRSTITLSQNKNVQVILSSPTAQSVP   500
 501  SNGQNQIGVEHIDLLEDDLEKDAILDDSMSFSFGRQHMPMSHSDLELIDS   550
 551  EKENEDFEEDNNNNGIEYLSDSDLERFDEERENRTQVADIQELDNDLKII   600
 601  TERKLTGDNEHPPPSWSPKIKREKSSVSQKDEEDDFDDDFSLSDIVSKSN   650
 651  LSSKTNGPTYPWSDEVLYRLHEVFKLPGFRPNQLEAVNATLQGKDVFVLM   700
 701  PTGGGKSLCYQLPAVVKSGKTHGTTIVISPLISLMQDQVEHLLNKNIKAS   750
 751  MFSSRGTAEQRRQTFNLFINGLLDLVYISPEMISASEQCKRAISRLYADG   800
 801  KLARIVVDEAHCVSNWGHDFRPDYKELKFFKREYPDIPMIALTATASEQV   850
 851  RMDIIHNLELKEPVFLKQSFNRTNLYYEVNKKTKNTIFEICDAVKSRFKN   900
 901  QTGIIYCHSKKSCEQTSAQMQRNGIKCAYYHAGMEPDERLSVQKAWQADE   950
 951  IQVICATVAFGMGIDKPDVRFVYHFTVPRTLEGYYQETGRAGRDGNYSYC  1000
1001  ITYFSFRDIRTMQTMIQKDKNLDRENKEKHLNKLQQVMAYCDNVTDCRRK  1050
1051  LVLSYFNEDFDSKLCHKNCDNCRNSANVINEERDVTEPAKKIVKLVESIQ  1100
1101  NERVTIIYCQDVFKGSRSSKIVQANHDTLEEHGIGKSMQKSEIERIFFHL  1150
1151  ITIRVLQEYSIMNNSGFASSYVKVGPNAKKLLTGKMEIKMQFTISAPNSR  1200
1201  PSTSSSFQANEDNIPVIAQKSTTIGGNVAANPPRFISAKEHLRSYTYGGS  1250
1251  TMGSSHPITLKNTSDLRSTQELNNLRMTYERLRELSLNLGNRMVPPVGNF  1300
1301  MPDSILKKMAAILPMNDSAFATLGTVEDKYRRRFKYFKATIADLSKKRSS  1350
1351  EDHEKYDTILNDEFVNRAAASSNGIAQSTGTKSKFFGANLNEAKENEQII  1400
1401  NQIRQSQLPKNTTSSKSGTRSISKSSKKSANGRRGFRNYRGHYRGRK     1447

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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