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

NucPred

Fetching Q8HZK3 from www.uniprot.org...

The NucPred score for your sequence is 0.72 (see score help below)

   1  MGFRLALAWTLLVGPWMPMGARNSISWEVQRFDGWYNNLMEHKWGSKGSR    50
  51  LQRLVPASYADGVYQPLGEPHLPNPRDLSNTAMRGPAGQASLRNRTVLGV   100
 101  FFGYHVLSDLVSIEKPGCPAEFLNIHIPPGDPVFDPHKSGDVVLPFQRSR   150
 151  WDPNTGQSPSNPRDLTNEVTGWLDGSAIYGSSHSWSDELRSFSGGQLASG   200
 201  PDPAFPRQAQDPLFMWTPPDPATGQRGPQGLYAFGAEQGNREPFLQALGL   250
 251  LWFRYHNLCAQKLAREHPLWGDEELFQHARKRVIATYQSITMYEWLPSFL   300
 301  RKMPQEYTGYRPFLDPSISPEFLAASEQFFSTMVPPGVYMRNASCHFQGV   350
 351  INRNSSVSRALRVCNSYWSREHPNLQRAEDVDALLLGMASQIAEREDHMV   400
 401  VEDVQDFWPGPLKFSRTDHLASCLQRGRDLGLPSYTKARARLGLPPVTRW   450
 451  QDINPALSRSDGIVLEATAALYNQDLSRLELLPGGLLESYGDPGPLFSTI   500
 501  VLDQFVRLRDGDRYWFENTKNGLFSEKEIAEIRNTSLRDVLVAVTNMTPG   550
 551  ALQPNVFFWHAGDPCPQPRQLSTKDLPACAPLIMRDYFKGSGFGFGVTIG   600
 601  TLCCFPLVSLLSAWIVAQLRRRNFKRLQVQNRQSIMCEKLVGGMKALEWQ   650
 651  GRKEPCRPVLVHLQSGQIHVMDGRLSVLRTIQLRPPQQVNLILSSNHGRR   700
 701  TLLLKIPKEYDLVLMFDLEEERQVMVENLQSALKESGLSFQEWELREQEL   750
 751  MRAAVTREQRSHLLETFFRHLFSQVLDIDQADAGALPLDSSQKVREALTC   800
 801  ELSRAEFAESLGLKPQDMFVESMFSLADKDGNGYLSFREFLDILVVFMKG   850
 851  SPEEKSRLMFRMYDFDGNGLISKDEFIRMLRSFIEISNNCLSKAQLTEVV   900
 901  ESMFREAGFQDKQELTWEDFHFMLRDHDSELRFTQLCVKGVEVPEVIKDL   950
 951  CRRASYISQEKLCPSPRVSAHCPRSNVDVEVELTPWKLQCPTDTDPPQEI  1000
1001  RRRFGKKVTSFQPLLFTEAHREKFQRSRRHQTVQQFKRFVENYRRHIGCL  1050
1051  AVFYTIAGGLFLERAYYYAFAAHHMGITDTTRVGIILSRGTAASISFMFS  1100
1101  YILLTMCRNLITFLRETFLNRYVPFDAAVDFHRLIASTAIILTVLHSAGH  1150
1151  VVNVYLFSISPLSVLSCLFPGLFHDNGSEFPQKYYWWFFQTVPGLTGVML  1200
1201  LLILAIMYVFASHHFRRCSFRGFWLTHHLYILLYMLLIIHGSFALIQLPR  1250
1251  FHIFFLVPALIYVGDKLVSLSRKKVEISVVKAELLPSGVTHLQFQRPQGF  1300
1301  EYKSGQWVRIACLALGTTEYHPFTLTSAPHEDTLSLHIRAAGPWTTRLRE  1350
1351  IYSPPTDDNCAKYPKLYLDGPFGEGHQEWHKFEVSVLVGGGIGVTPFASI  1400
1401  LKDLVFKSSVSCQVFCKKIYFIWVTRTQRQFEWLADIIREVEENDHRDLV  1450
1451  SVHIYITQLAEKFDLRTTMLYICERHFQKVLNRSLFTGLRSITHFGRPPF  1500
1501  EPFFNSLQEVHPQVRKIGVFSCGPPGMTKNVEKACQLINRQDRTHFSHHY  1550
1551  ENF                                                 1553

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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