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

NucPred

Fetching Q9JIR4 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MSSAVGPRGPRPPTVPPPMQELPDLSHLTEEERNIIMAVMDRQKEEEEKE    50
  51  EAMLKCVVRDMAKPAACKTPRNAESQPHQPPLNIFRCVCVPRKPSSEEGG   100
 101  PERDWRLHQQFESYKEQVRKIGEEARRYQGEHKDDAPTCGICHKTKFADG   150
 151  CGHLCSYCRTKFCARCGGRVSLRSNNEDKVVMWVCNLCRKQQEILTKSGA   200
 201  WFFGSGPQQPSQDGTLSDTATGAGSEVPREKKARLQERSRSQTPLSTAAV   250
 251  SSQDTATPGAPLHRNKGAEPSQQALGPEQKQASRSRSEPPRERKKAPGLS   300
 301  EQNGKGGQKSERKRVPKSVVQPGEGIADERERKERRETRRLEKGRSQDYS   350
 351  DRPEKRDNGRVAEDQKQRKEEEYQTRYRSDPNLARYPVKAPPEEQQMRMH   400
 401  ARVSRARHERRHSDVALPHTEAAAAAPAEATAGKRAPATARVSPPESPRA   450
 451  RAAAAQPPTEHGPPPPRPAPGPAEPPEPRVPEPLRKQGRLDPGSAVLLRK   500
 501  AKREKAESMLRNDSLSSDQSESVRPSPPKPHRPKRGGKRRQMSVSSSEEE   550
 551  GVSTPEYTSCEDVELESESVSEKGDLDYYWLDPATWHSRETSPISSHPVT   600
 601  WQPSKEGDRLIGRVILNKRTTMPKESGALLGLKVVGGKMTDLGRLGAFIT   650
 651  KVKKGSLADVVGHLRAGDEVLEWNGKPLPGATNEEVYNIILESKSEPQVE   700
 701  IIVSRPIGDIPRIPESSHPPLESSSSSFESQKMERPSISVISPTSPGALK   750
 751  DAPQVLPGQLSVKLWYDKVGHQLIVNVLQATDLPPRVDGRPRNPYVKMYF   800
 801  LPDRSDKSKRRTKTVKKLLEPKWNQTFVYSHVHRRDFRERMLEITVWDQP   850
 851  RVQDEESEFLGEILIELETALLDDEPHWYKLQTHDESSLPLPQPSPFMPR   900
 901  RHIHGESSSKKLQRSQRISDSDISDYEVDDGIGVVPPVGYRASARESKAT   950
 951  TLTVPEQQRTTHHRSRSVSPHRGDDQGRPRSRLPNVPLQRSLDEIHPTRR  1000
1001  SRSPTRHHDASRSPADHRSRHVESQYSSEPDSELLMLPRAKRGRSAESLH  1050
1051  MTSELQPSLDRARSASTNCLRPDTSLHSPERERHSRKSERCSIQKQSRKG  1100
1101  TASDADRVLPPCLSRRGYATPRATDQPVVRGKYPTRSRSSEHSSVRTLCS  1150
1151  MHHLAPGGSAPPSPLLLTRTHRQGSPTQSPPADTSFGSRRGRQLPQVPVR  1200
1201  SGSIEQASLVVEERTRQMKVKVHRFKQTTGSGSSQELDHEQYSKYNIHKD  1250
1251  QYRSCDNASAKSSDSDVSDVSAISRASSTSRLSSTSFMSEQSERPRGRIS  1300
1301  SFTPKMQGRRMGTSGRAIIKSTSVSGEIYTLERNDGSQSDTAVGTVGAGG  1350
1351  KKRRSSLSAKVVAIVSRRSRSTSQLSQTESGHKKLKSTIQRSTETGMAAE  1400
1401  MRKMVRQPSRESTDGSINSYSSEGNLIFPGVRVGPDSQFSDFLDGLGPAQ  1450
1451  LVGRQTLATPAMGDIQIGMEDKKGQLEVEVIRARSLTQKPGSKSTPAPYV  1500
1501  KVYLLENGACIAKKKTRIARKTLDPLYQQSLVFDESPQGKVLQVIVWGDY  1550
1551  GRMDHKCFMGVAQILLEELDLSSMVIGWYKLFPPSSLVDPTLAPLTRRAS  1600
1601  QSSLESSSGPPCIRS                                     1615

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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