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

NucPred

Fetching Q8WNU5 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MKPVKHLLTTSNKSATLPALTSKKGLHNLPLSPKLKEKHNAKLIHDKIEP    50
  51  MVLRSPPTGESIVRYALPIPSSKTKNLLPGDEMIGKIIKHLKMVVSTLEE   100
 101  TYGHCDQNGEEPFVKRENEELSLSIGDDMNSFLTCCSQFATQLETALKEE   150
 151  QNVCILHYFFFCPSFVFLKWFQWQVNQMEEISKDQTLLQAEPPEPDKTVT   200
 201  LSIAQIVRLLQRFEELKNRLKQRSKSSWKVMLSKTMDEENRPEAVKSCEA   250
 251  VAQKIEEFIEAHSTDEFKGVSATEPQTAHSMTNRFNTMLKVFENQANMLE   300
 301  RAVNDQVLLDAEYKQIQRDFELLSEEKLVLENELQKLKDTEKIKSTNNRT   350
 351  KKAAKTVKKKDKGKSEDSEKKMSSEKEFKIKDLDQVQKVARLEIENKVLQ   400
 401  EQLKQALQEAEKAKHQLNYFLSQERKLLKSEGKTETTMRVGNSQTEVKGE   450
 451  DSKTIPLEKETGKSLVSDSGGQKTSDKIQEYPQITAQSGRLIEKSSEKKR   500
 501  SSPAISDLSQILKSQDESAFLESSNEVSVAENQSNKSPSETRDESLTTVS   550
 551  SSKEVQDSLSVGTLAQKNETVMSPFILPPVLTESKKADVSEEQLQKKTEE   600
 601  QTYQAPEKSQAYSEVPDENLMVENKDSVTKVQVEQMKQTTSSMERREATL   650
 651  TTPQSPEDVVLVSRSQSETKNLEATGNESFHSHNDVPEENLMLEQDTKSK   700
 701  TEVEVKKQKSFQDNQLNTHNEVPNERLIVEHQESMSKTKLQVKKQETSTE   750
 751  QPLTTHDKEPDENLTLGHQDSMSKSEMQVKEQSTLKGQRITTHEEEPGKN   800
 801  LALEHQDSLSKLEMQIKKNEKLPREKRHSTHGEESSENPMLKHQDAVSKI   850
 851  QVQLEKQETSEGGRSIPDKNSMFVHQDSVSKLQMQEKKKVTPGRERRNTH   900
 901  IVVPNENVVSVHQDSKSKLQMQEKKQINPGVEKHKTFPFEIQKKDISLEH   950
 951  LLPEEKVLLSRRESQTKKLQAKVTSRKITNEAASELPNTAENLPAVYPSI  1000
1001  SDLIIRLDLNKVVETDIESLRGALGRRLLNDEFKTQPKSFPGSEIEQLTD  1050
1051  AFGRDILKDEFKTRSKSLPETDERLRRATERGTINNAMKTQLKRKSHPET  1100
1101  GLKHLKGVNEKDIIKDLINIQSKRHAETDKEHLADAIGRGIIKGSINAQL  1150
1151  KGHQETDKNFFAYAIGRGVRKESIKTQLKSHPETDKEFLADAIGRGIIIG  1200
1201  PIIRQLKSHQETDKQLLKDAIGRDIIKGPINAQLKSHQETDVEPLTNAIG  1250
1251  SSKTIGEIKTQLRTHYDVNLFKNKDMSIQRQEGIFNRSITPSKFPTKVIN  1300
1301  LSPFENKEETYEYSSPYAIAPSKAVYRTYRASSSFSKDIHLPLLNQLHSG  1350
1351  HSKVVTLNQKTIEFTLPSVTNTIGKPAYKVLHAAARKSVPHPYF        1394

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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