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

NucPred

Fetching Q96RT1 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MTTKRSLFVRLVPCRCLRGEEETVTTLDYSHCSLEQVPKEIFTFEKTLEE    50
  51  LYLDANQIEELPKQLFNCQSLHKLSLPDNDLTTLPASIANLINLRELDVS   100
 101  KNGIQEFPENIKNCKVLTIVEASVNPISKLPDGFSQLLNLTQLYLNDAFL   150
 151  EFLPANFGRLTKLQILELRENQLKMLPKTMNRLTQLERLDLGSNEFTEVP   200
 201  EVLEQLSGLKEFWMDANRLTFIPGFIGSLKQLTYLDVSKNNIEMVEEGIS   250
 251  TCENLQDLLLSSNSLQQLPETIGSLKNITTLKIDENQLMYLPDSIGGLIS   300
 301  VEELDCSFNEVEALPSSIGQLTNLRTFAADHNYLQQLPPEIGSWKNITVL   350
 351  FLHSNKLETLPEEMGDMQKLKVINLSDNRLKNLPFSFTKLQQLTAMWLSD   400
 401  NQSKPLIPLQKETDSETQKMVLTNYMFPQQPRTEDVMFISDNESFNPSLW   450
 451  EEQRKQRAQVAFECDEDKDEREAPPREGNLKRYPTPYPDELKNMVKTVQT   500
 501  IVHRLKDEETNEDSGRDLKPHEDQQDINKDVGVKTSESTTTVKSKVDERE   550
 551  KYMIGNSVQKISEPEAEISPGSLPVTANMKASENLKHIVNHDDVFEESEE   600
 601  LSSDEEMKMAEMRPPLIETSINQPKVVALSNNKKDDTKETDSLSDEVTHN   650
 651  SNQNNSNCSSPSRMSDSVSLNTDSSQDTSLCSPVKQTHIDINSKIRQEDE   700
 701  NFNSLLQNGDILNSSTEEKFKAHDKKDFNLPEYDLNVEERLVLIEKSVDS   750
 751  TATADDTHKLDHINMNLNKLITNDTFQPEIMERSKTQDIVLGTSFLSINS   800
 801  KEETEHLENGNKYPNLESVNKVNGHSEETSQSPNRTEPHDSDCSVDLGIS   850
 851  KSTEDLSPQKSGPVGSVVKSHSITNMEIGGLKIYDILSDNGPQQPSTTVK   900
 901  ITSAVDGKNIVRSKSATLLYDQPLQVFTGSSSSSDLISGTKAIFKFDSNH   950
 951  NPEEPNIIRGPTSGPQSAPQIYGPPQYNIQYSSSAAVKDTLWHSKQNPQI  1000
1001  DHASFPPQLLPRSESTENQSYAKHSANMNFSNHNNVRANTAYHLHQRLGP  1050
1051  ARHGEMWAISPNDRLIPAVTRSTIQRQSSVSSTASVNLGDPGSTRRAQIP  1100
1101  EGDYLSYREFHSAGRTPPMMPGSQRPLSARTYSIDGPNASRPQSARPSIN  1150
1151  EIPERTMSVSDFNYSRTSPSKRPNARVGSEHSLLDPPGKSKVPRDWREQV  1200
1201  LRHIEAKKLEKKHPQTSSSGDPCQDGIFISGQQNYSSATLSHKDVPPDSL  1250
1251  MKMPLSNGQMGQPLRPQANYSQIHHPPQASVARHPSREQLIDYLMLKVAH  1300
1301  QPPYTQPHCSPRQGHELAKQEIRVRVEKDPELGFSISGGVGGRGNPFRPD  1350
1351  DDGIFVTRVQPEGPASKLLQPGDKIIQANGYSFINIEHGQAVSLLKTFQN  1400
1401  TVELIIVREVSS                                        1412

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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