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

NucPred

Fetching P23678 from www.uniprot.org...

The NucPred score for your sequence is 0.73 (see score help below)

   1  MSSVKVAVRVRPFNQREISNTSKCVLQVNGNTTTINGHSINKENFSFNFD    50
  51  HSYWSFARNDPHFITQKQVYEELGVEMLEHAFEGYNVCIFAYGQTGSGKS   100
 101  YTMMGKANDPDEMGIIPRLCNDLFARIDNNNDKDVQYSVEVSYMEIYCER   150
 151  VKDLLNPNSGGNLRVREHPLLGPYVDDLTKMAVCSYHDICNLMDEGNKAR   200
 201  TVAATNMNSTSSRSHAVFTIVLTQKRHCADSNLDTEKHSKISLVDLAGSE   250
 251  RANSTGAEGQRLKEGANINKSLTTLGLVISKLAEESTKKKKSNKGVIPYR   300
 301  DSVLTWLLRENLGGNSKTAMLAALSPADINFDETLSTLRYADRAKQIVCQ   350
 351  AVVNEDPNAKLIRELNEEVIKLRHILKDKGIDVTDVQETPGKHKKGPKLP   400
 401  AHVHEQLEKLQESEKLMAEIGKTWEQKLIHTEEIRKQREEELRDMGLACA   450
 451  EDGTTLGVFSPKKLPHLVNLNEDPLMSECLIYYLKEGVTSVGRPEAEHRP   500
 501  DILLSGEAILELHCEFINEDGNVTLTMKPNASCYINGKQVTTPTVLHTGS   550
 551  RVILGEHHVFRYNDPQEARQSRHNLAAIAEQPIDWKYAQQELLDKQGIDL   600
 601  KADMEKKMLEMESQYRREKVELEQKMYHQTREYESMIENLQKQVDLAQSY   650
 651  ISGGGSIWEGERMLTSSLLEFPEELKWTSDQKRVVLKAAIKWRYHQFTSV   700
 701  RDDLWGNAIFVKEANAISVELKKKVQFQFALLTDTMYSPLPPDLLPPGED   750
 751  LTLRPYPKTVVAIQVQDLKNGATHYWSIEKLKQRLEAMRDMYETDAEMSP   800
 801  ADGDPMMDALMGTDPFYDRFPWFRMVGRAFVYLNNLLHNVPLIHKVAVVN   850
 851  EKGEVKGYLKVAIEPVQKDEVINQKKGVRQTAKLHFRKEDFLKSHKNGET   900
 901  SDSDALAFPEHMQEEVEFCFRVVVLQAIDVADTYSDVFCQFNFLHRHDEA   950
 951  FSTEPMKNSKSPLTFEHTQNLHIKMSKTFLHYLHHFPIIFEVFGHFQPKS  1000
1001  EQFNFERQNSALGRRLSTKLTFQQPSLVISTPVKSKKANAPIQNNNASVK  1050
1051  SKHDLLVWFEICELANNGEYVPTIVDHAQGLPTHGIFLLHQGIQRRIKIT  1100
1101  ICHEKGELKWKDCQELVVGRIRAGPEWAGGDDVDVLSLGLFPGTFMEFSM  1150
1151  DDRTFFQFEAAWDSSLHNSPLLNRVSNYGDQIYMTLSAYMELDGCAQPAV  1200
1201  VTKDLCLLIYARDSKISAASRFCRSLVGGISKSPEMNRVPGVYQLCLKDG  1250
1251  SDSGSPGAIRRQRRVLDTSSAYVRGEENLGQWRPRGDSLIFEHQWELEKL  1300
1301  TRLQQVERVRLFLRLRDRLKGKKNKGEARTPVSPCDPVCAIPESIKLDEK  1350
1351  DKGIVGKVLGLIRRKIPMNKDPPTGNKAQELSDESGSNSITSPVSDKSLI  1400
1401  KSSRSSDLLCRQKSKSDQNLASNDDIVDNLGGMKRSLSGSRILQLNILVP  1450
1451  EVLEERVGVVVSKKGYMNFLEEKTQGWTRRWVIVRRPYILLFRDDRDLVI  1500
1501  RGIINLANARIEHSEDQQAMVKVPNTFSVCTNQRGFLMQMMPGDEMYDWL  1550
1551  YAINPLMAGQMKLHGNQNGTTLKSPTSSSSIAAS                  1584

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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