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

NucPred

Fetching Q80U22 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MDSPPKLTGETLIVHHIPLVHCQVPDRQCCGGAGGGGGGTRANPFCPPEL    50
  51  GLTQPDHDLGQADSLLYPSLHSAPGAPTGSSDSVKSRSRDGRGPGAPKRH   100
 101  NPFLVQEGVGETGLGDLHDSSTGDSVTQQSFHLHSASQPFHLSSFQLPPS   150
 151  GPGQGRPWGATHSRPGVVEGQEQDPATALGTQCSTSHCCRPELEAERMEL   200
 201  DECGGHGGSGSGGGTSDISGFSFEQEWKISSDESPRHPGRSGSGTQHCHC   250
 251  SSTSSQSEAADQSMGYVSDSSCNSSDGVLVTFSTLYNKMHSSSRANLNSV   300
 301  PQSCSDSSFCSHADPGAFYLDLQPSPAESRMSCESHHPENGDREEGCGCP   350
 351  HVSSPELDANCNAYHPHSEPCPAVADLTACFQSQARLVVATQNYYKLVTC   400
 401  DLSSQSSPSPAGSSITSCSEEHTKISPPPGPCPDPDPNQPSEYYLFQKPD   450
 451  IQPEEQEAVGSPAEAATAMGPTVLEGQVYTNTSPPNLNTGRQRSRSYDRS   500
 501  LERSPPVRLGSLERMLSCPVRLSEGPAALAGPASPPRRVTSFAELAKGRK   550
 551  KAAGSGSPPLRASVGDSSQEFSPIQEAQQDRAAPLDEGTRCSHSLPSLPL   600
 601  GPSLDLLGPEPWSTPVCQGSQSSEMPLPSLRAAGQGPLAQLMDPGPAFSG   650
 651  SPATSHTQRDSRARADGGGTESRPVLRYSKEQRPTTLPIQPFVFQHHFPK   700
 701  QLAKARALHSLSQLYSLSGCSRAQQPAPLVISTAQGPAPAPSGEPQPFTS   750
 751  QASGRGARNAGPEPETSRPSPLGSYSPVRSAGPFGSSTDSSASTSCSPPP   800
 801  EQGTAADSVSPWSHTCPPTVRPATSQQPPKEDQKIPTLAEYRLHGTGSLP   850
 851  PLGSWRSGFTRAESLVRGGGEGSMANRPNNANHLSPQALKWREYRRKNPL   900
 901  GPPGLSGSLDRRPPEARLARRNPIFEFPGSFGTTSHLNCRLNGQISKPLS   950
 951  LTCPDLQDPFSLTEKPPAEFCLSPDGNSEAISIDILQKKGLVKAVNTAVD  1000
1001  LIVAHFGTSRDPGVKAKLGNSSVSPNVGHLVLKYLCPAVQAVLEDGLKAF  1050
1051  VLDVIIGQRKNMPWSVVEASTQLGPSTKVLHGLYNKVSQFPELTSHTMRF  1100
1101  NAFILGLLNIRSLEFWFNHLYNHEDIIQTHYQPWGFLRAAHTVCPGLFEE  1150
1151  LLLLLQPLALLPFSLDLLFQHRLLQSGRQQRQHKELLRVSQDLLLSAHST  1200
1201  LQLARSRGQEGPGDMDRVAPGERVKGVGASEGGEEDEEDAEEVAVVAGSS  1250
1251  DHGKWARGGQAGWWYQLMQSSQVYIDGTAEGSRFPRSSSSSSGSGSEKKK  1300
1301  GVGSGGPSQAPPPPPREGVVEGAEACPAPEEALGQERGWPFWMGSPPDSV  1350
1351  LAELRRSREREGPVAPPTENEEGTAEPSPGGIKWGHLFGSRKSQREARPT  1400
1401  NRLPSDWLSLDKSVFQLVAQTMGARREPEPRENLQESHPPAVPSKPPCEV  1450
1451  QALCHHLATGPGQLSFHKGDILRVLGPARGDWLRCSRGPDTGLVPLAYVT  1500
1501  LPPTPSSPPGSSQN                                      1514

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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