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

NucPred

Fetching Q8GU87 from www.uniprot.org...

The NucPred score for your sequence is 0.35 (see score help below)

   1  MWAAEAAFARSGSWREEEDEQEALRWAALQRLPTVARARRGLLRSPAPGE    50
  51  DRVQGDDALCEVDVAGLSPGDRTALVDRLLADSGDVEDFFRRIRSRFDAV   100
 101  QIEFPKIEVRYEDLTVDAYVHVGSRALPTIPNFICNMTEAFLRHLRIYRG   150
 151  GRVKLPILDNVSGIIRPSRMTLLLGPPSSGKTTLLLALAGRLGPGLKVSG   200
 201  NITYNGHHLNEFVPQRTSAYVSQQDWHASEMTVRETLEFAGRCQGVGIKY   250
 251  DMLVELLRREKNEGIKPDEDLDVFMKALALEGKQTSLVAEYIMKVYGLDI   300
 301  CADTIVGDEMIKGISGGQKKRLTTGELLVGSARVLFMDEISTGLDSATTY   350
 351  QIIKYLRHSTHALDGTTIISLLQPAPETYELFDDVILISEGQIVYQGPRE   400
 401  YAVDFFAGMGFRCPERKNVADFLQEVLSKKDQQQYWCHYDYPYQYVSVSK   450
 451  FAEAFKTFVIGKRLHDELAVPYNRHRNHPAALSTSNYGVRRLELLKSNFQ   500
 501  WQHLLMKRNSFIYVFKFIQLLLVALITMTVFFRSTMHRDSVDDGIIYLGA   550
 551  LYFAIVMILFNGFTEVSLLVTKLPILYKHRDLHFYPPWAYTLPSWLLSIP   600
 601  TSLIESGMWVLVTYYVVGYDPQFTRCLGQFLLLFFLHQTSLALFRVMASL   650
 651  GRNMIVANTFGSFALLVVMILGGFIITKESIPAWWIWGYWISPMMYAQNA   700
 701  ISVNEFLGHSWSQQFANQNITLGEAILTGYGLFKEKYWFWIGVGALFGYA   750
 751  IVLNFLFTLFLTLLNPIGNIQAVVSKDDIQHRAPRRKNGKLALELRSYLH   800
 801  SASLNGHNLKDQKGMVLPFQPLSMCFKNINYYVDVPAELKSQGIVEDRLQ   850
 851  LLIDVTGAFRPGILTALVGVSGAGKTTLMDVLAGRKTGGLIEGSITISGY   900
 901  PKNQETFTRISGYCEQNDVHSPCLTVIESLLYSACLRLPSHVDVNTRRVF   950
 951  VEEVMELVELNALSGALVGLPGVNGLSTEQRKRLTIAVELVANPSIVFMD  1000
1001  EPTSGLDARSAAIVMRTVRNIVNTGRTIVCTIHQPSIDIFESFDELLFMK  1050
1051  RGGQLIYAGPLGSKSRNLVEFFEAIPGVPKIRDGYNPAAWMLEVTSTQME  1100
1101  QILGVDFAEYYRQSKLFQQTQEMVDILSRPRRESKELTFATKYSQPFFAQ  1150
1151  YAACLWKQNLSYWRNPQYTAVRFFYTVIISLMFGTICWKFGSRRETQHDI  1200
1201  FNAMGAMYAAVLFIGITNATSVQPVISIERFVSYRERAAGMYSALPFAFS  1250
1251  LVTVEFPYILVQSLIYGTIFYSLGSFEWTAVKFLWYLFFMYFTLLYFTFY  1300
1301  GMMTTAITPNHTVAPIIAAPFYTLWNLFCGFMIPRKRIPAWWRWYYWANP  1350
1351  VSWTLYGLLTSQFGDLDQPLLLADGITTTTAVDFLRDHFGFRHDFLGVVA  1400
1401  GMVAGFCVLFAVVFALAIKYLNFQRR                          1426

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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