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

NucPred

Fetching Q92729 from www.uniprot.org...

The NucPred score for your sequence is 0.46 (see score help below)

   1  MARAQALVLALTFQLCAPETETPAAGCTFEEASDPAVPCEYSQAQYDDFQ    50
  51  WEQVRIHPGTRAPADLPHGSYLMVNTSQHAPGQRAHVIFQSLSENDTHCV   100
 101  QFSYFLYSRDGHSPGTLGVYVRVNGGPLGSAVWNMTGSHGRQWHQAELAV   150
 151  STFWPNEYQVLFEALISPDRRGYMGLDDILLLSYPCAKAPHFSRLGDVEV   200
 201  NAGQNASFQCMAAGRAAEAERFLLQRQSGALVPAAGVRHISHRRFLATFP   250
 251  LAAVSRAEQDLYRCVSQAPRGAGVSNFAELIVKEPPTPIAPPQLLRAGPT   300
 301  YLIIQLNTNSIIGDGPIVRKEIEYRMARGPWAEVHAVSLQTYKLWHLDPD   350
 351  TEYEISVLLTRPGDGGTGRPGPPLISRTKCAEPMRAPKGLAFAEIQARQL   400
 401  TLQWEPLGYNVTRCHTYTVSLCYHYTLGSSHNQTIRECVKTEQGVSRYTI   450
 451  KNLLPYRNVHVRLVLTNPEGRKEGKEVTFQTDEDVPSGIAAESLTFTPLE   500
 501  DMIFLKWEEPQEPNGLITQYEISYQSIESSDPAVNVPGPRRTISKLRNET   550
 551  YHVFSNLHPGTTYLFSVRARTGKGFGQAALTEITTNISAPSFDYADMPSP   600
 601  LGESENTITVLLRPAQGRGAPISVYQVIVEEERARRLRREPGGQDCFPVP   650
 651  LTFEAALARGLVHYFGAELAASSLPEAMPFTVGDNQTYRGFWNPPLEPRK   700
 701  AYLIYFQAASHLKGETRLNCIRIARKAACKESKRPLEVSQRSEEMGLILG   750
 751  ICAGGLAVLILLLGAIIVIIRKGRDHYAYSYYPKPVNMTKATVNYRQEKT   800
 801  HMMSAVDRSFTDQSTLQEDERLGLSFMDTHGYSTRGDQRSGGVTEASSLL   850
 851  GGSPRRPCGRKGSPYHTGQLHPAVRVADLLQHINQMKTAEGYGFKQEYES   900
 901  FFEGWDATKKKDKVKGSRQEPMPAYDRHRVKLHPMLGDPNADYINANYID   950
 951  GYHRSNHFIATQGPKPEMVYDFWRMVWQEHCSSIVMITKLVEVGRVKCSR  1000
1001  YWPEDSDTYGDIKIMLVKTETLAEYVVRTFALERRGYSARHEVRQFHFTA  1050
1051  WPEHGVPYHATGLLAFIRRVKASTPPDAGPIVIHCSAGTGRTGCYIVLDV  1100
1101  MLDMAECEGVVDIYNCVKTLCSRRVNMIQTEEQYIFIHDAILEACLCGET  1150
1151  TIPVSEFKATYKEMIRIDPQSNSSQLREEFQTLNSVTPPLDVEECSIALL  1200
1201  PRNRDKNRSMDVLPPDRCLPFLISTDGDSNNYINAALTDSYTRSAAFIVT  1250
1251  LHPLQSTTPDFWRLVYDYGCTSIVMLNQLNQSNSAWPCLQYWPEPGRQQY  1300
1301  GLMEVEFMSGTADEDLVARVFRVQNISRLQEGHLLVRHFQFLRWSAYRDT  1350
1351  PDSKKAFLHLLAEVDKWQAESGDGRTIVHCLNGGGRSGTFCACATVLEMI  1400
1401  RCHNLVDVFFAAKTLRNYKPNMVETMDQYHFCYDVALEYLEGLESR      1446

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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