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

NucPred

Fetching Q98930 from www.uniprot.org...

The NucPred score for your sequence is 0.62 (see score help below)

   1  GWVSLNDSHNQMVVHWAGEKSNVIVALARDSLSLLGPKNSDVYISYDYGK    50
  51  SFKKISERFSFGDGNSSAVAIAQFYHSPANNQRYIFVDAFVPYLWITTDF   100
 101  CKSIQGFSIPFRAADLLLHSRNPNLVLGFDRSHPNKQLWKSDDFGQTWIM   150
 151  IQEHVKSFSWGVEPYDKPNTVYIERHEPSGTSTVIRSTDFFQSRENKEVI   200
 201  LEDVDDFQLRDKYLFATKAVRLLGSLQPSSVQLWVSFNRKPMRVAQFVTK   250
 251  HPIKEYYIADASEDQVFVCVSHDDNRTNLYISEAEGLKFSLSLENVLYYS   300
 301  PGGAGSDTLVRYFANEPFADFHRVEGVRGVYIATLLNGSFSEENMRSVIT   350
 351  FDKGGTWEPLQPPAETRYGEKTHCELSQGCSLHLAQRLSQLLNFQLRRMP   400
 401  ILSKESAPGLIIATGSIGKSMAKKTNVYISSSAGARWREALSGPHYYTWG   450
 451  DHGGILVAIAQGTETDQLKYSTNEGETWKSFTFSEKPVFVYGLLTEPGEK   500
 501  STIFTIFGSYKENGHSWLILQVNTSDVLGVPCTENDYKLWSPSDERGNEC   550
 551  LLGHKTVFKRRTPHATCFNGEDFDRPVMVSNCSCTREDFECDFGFKLSED   600
 601  LSLEVCVPDPEFAGKPYDPPVPCPVGSTYRRTRGYRKISGDTCMGGDIES   650
 651  RLEGEMLPCPLAEENEFILYATRYSIHRYDLASGLSQELPLAGLRGAVAL   700
 701  DFDYEHNCLYWADVTLDIIQRLCLNGSSGQEIIISTGLETVEALAFEPLS   750
 751  QLLYWVNAGIPKIEVANPDGDLRLTVLNSSVLERPRALALVPREGLMFWT   800
 801  DWGDSRPGIYRSDMDGSLAACIVSEGVRWPNGISVDDHWIYWTEAYMDRI   850
 851  ERVDFNGLQRSVILDSLPHPYAIAVFKNEIYWNDWSQLSIFRASKNSGSR   900
 901  METLVGRLYGIMDMKIFYRGKTTGQNACIAHPCSLLCLPKSNNGRSCKCP   950
 951  EGVSSTVLPSGEVKCDCPHGYSMKNNTCVKEENTCLPNQYRCFNGNCINS  1000
1001  IWQCDNNNDCGDMSDEKNCPTTVCDAETQFRCRESGTCIPLSYKCDLEDD  1050
1051  CGDNSDESHCEAHQCRKDEFSCSSGMCIRLSWRCDDDNDCRDWSDEANCT  1100
1101  MFRTCEASSFQCLNGHCIPQRWACDGDADCQDGSDEDPTICEKKCNGFQC  1150
1151  PNGTCISTSKHCNGITDCADASDEQDCEIPLCTRYMDFVCKNRQQCLSHS  1200
1201  MVCDGDIQCEDGSDEDANYAGCAQEPEFHRTCDQFSFQCANGVCISLVWK  1250
1251  CDGMDDCGDYSDEASCENPTDAPTCSRYYQFQCGNGHCIPNQWKCDGEND  1300
1301  CGDWSDEKECEGSPLLPITTAVPPTCLPNHFRCGSGACITNSWVCDGYRD  1350
1351  CADGSDEDACPTSHPNVTSSPPAPRGRCSRTEFECQQLHKCIPNWKRCDG  1400
1401  RRDCQDGTDERSCPTHSSLSCPQGYRCEDGEACLLATERCDGYLDCSDGS  1450
1451  DERNCTDDTIVYKVQNLQWTADFSGAITLTWARPKRMSSTSCVYNVYYRM  1500
1501  VGESIWKVLETHSNKTSSVLKVLKPDCTYQVKVQVQCLSRVYNTNDFITL  1550
1551  RVPEGLPDAPFNLQLALKKEAEGVVLCSWSAPVNAHGLIREP          1592

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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