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

NucPred

Fetching Q12275 from www.uniprot.org...

The NucPred score for your sequence is 0.83 (see score help below)

   1  MDFSIPPTLPLDLQSRLNELIQDYKDENLTRKGYETKRKQLLDKFEISQM    50
  51  RPYTPLRSPNSRKSKHLHRRNTSLASSITSLPNSIDRRHSIYRVTTINST   100
 101  SANNTPRRRSKRYTASLQSSLPGSSDENGSVKDAVYNPMIPLLPRHTGAE   150
 151  NTSSGDSAMTDSLPLILRGRFEHYDGQTAMISINSKGKETFITWDKLYLK   200
 201  AERVAHELNKSHLYKMDKILLWYNKNDVIEFTIALLGCFISGMAAVPVSF   250
 251  ETYSLREILEIIKVTNSKFVLISNACHRQLDNLYSSSNHSKVKLVKNDVF   300
 301  QQIKFVKTDDLGTYTKAKKTSPTFDIPNISYIEFTRTPLGRLSGVVMKHN   350
 351  ILINQFETMTKILNSRSMPHWKQKSQSIRKPFHKKIMATNSRFVILNSLD   400
 401  PTRSTGLIMGVLFNLFTGNLMISIDSSILQRPGGYENIIDKFRADILLND   450
 451  QLQLKQVVINYLENPESAFSKKHKIDFSCIKSCLTSCTTIDTDVSEMVVH   500
 501  KWLKNLGCIDAPFCYSPMLTLLDFGGIFISIRDQLGNLENFPIHNSKLRL   550
 551  QNELFINREKLKLNEVECSITAMINSSSSFKDYLKLETFGFPIPDITLCV   600
 601  VNPDTNTLVQDLTVGEIWISSNHITDEFYQMDKVNEFVFKAKLNYSEMFS   650
 651  WAKYEMPTNEKSQAVTEQLDTILNICPANTYFMRTKLMGFVHNGKIYVLS   700
 701  LIEDMFLQNRLIRLPNWAHTSNLLYAKKGNQSAQPKGNTGAESTKAIDIS   750
 751  SLSGETSSGYKRVVESHYLQQITETVVRTVNTVFEVAAFELQHHKEEHFL   800
 801  VMVVESSLAKTEEESKNGETTDTTLMKFAETQRNKLETKMNDLTDQIFRI   850
 851  LWIFHKIQPMCILVVPRDTLPRRYCSLELANSTVEKKFLNNDLSAQFVKF   900
 901  QFDNVILDFLPHSAYYNESILSEHLSKLRKMALQEEYAMIEPAYRNGGPV   950
 951  KPKLALQCSGVDYRDESVDTRSHTKLTDFKSILEILEWRISNYGNETAFS  1000
1001  DGTNTNLVNSSASNDNNVHKKVSWASFGKIVAGFLKKIVGSKIPLKHGDP  1050
1051  IIIMCENSVEYVAMIMACLYCNLLVIPLPSVKESVIEEDLKGLVNIIQSY  1100
1101  KVKRVFVDAKLHSLLNDNNVVNKCFKKYKSLIPKITVFSKVKTKNALTVS  1150
1151  MFKNVLKQKFGAKPGTRIGMTPCVVWVNTEYDVTSNIHVTMTHSSLLNAS  1200
1201  KIVKETLQLRNNSPLFSICSHTSGLGFMFSCLLGIYTGASTCLFSLTDVL  1250
1251  TDPKEFLIGLQNLNVKDLYLKLETLYALLDRASSLIEGFKNKKENINSAK  1300
1301  NNTSGSLREDVFKGVRNIMIPFPNRPRIYTIENILKRYSTISLSCTQISY  1350
1351  VYQHHFNPLISLRSYLDIPPVDLYLDPFSLREGIIREVNPNDVSAGNYIK  1400
1401  IQDSGVVPVCTDVSVVNPETLLPCVDGEFGEIWCCSEANAFDYFVCNSSK  1450
1451  NKLYKDPFITEQFKSKMKSEVNNTLSYLRTGDLGFIKNVSCTNSQGEVVN  1500
1501  LNLLFVLGSIHESIEILGLTHFVSDLERTVKDVHSDIGSCLIAKAGGLLV  1550
1551  CLIRCKERHNPILGNLTTLIVSELLNKHGVILDLCTFVRTKGISPKNSSM  1600
1601  IMEVWAKNRASIMQAWFDQKIQIEAQFGINYGENISIYLLSDYEKDNI    1648

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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