 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q20745 from www.uniprot.org...
The NucPred score for your sequence is 0.36 (see score help below)
1 MAPATEADNNFDTHEWKSEFASTRSGRNSPNIFAKVRRKLLLTPPVRNAR 50
51 SPRLTEEELDALTGDLPYATNYTYAYSKIYDPSLPDHWEVPNLGGTTSGS 100
101 LSEQEHWSAASLSRQLLYILRFPVYLVLHVITYILEAFYHVIKITSFTIW 150
151 DYLLYLVKLAKTRYYAYQDHRRRTALIRNRQEPFSTKAARSIRRFFEILV 200
201 YVVLTPYRMLTRSNNGVEQYQYRSIKDQLENERASRMTTRSQTLERSRKF 250
251 DGLSKSPARRAAPAFVKTSTITRITAKVFSSSPFGEGTSENITPTVVTTR 300
301 TVKQRSVTPRFRQTRATREAITRALDTPELEIDTPLSTYGLRSRGLSHLN 350
351 TPEPTFDIGHAAATSTPLFPQETYNYQYEEATGNKIKTAFTWLGYLILFP 400
401 FFAARHVWYTFYDYGKSAYMKLTNYQQAPMETIHVRDINEPAPSSSDVHD 450
451 AVGVSWRIRIADFLSSFVATIVEAHQVVFAMFKGGIVETVSYFGGLFAGL 500
501 TDKKSSKFSWCQILGLLLALLFAIFLLGFLTSDNTAIRVKEITKDKNASK 550
551 KSEGSLPAVPIWISAANHVKHYTWMVKEFVVDIAFDTYNYGKSTIGRLGT 600
601 TPRYAWDLIASGCGAVGNGLKSVLSSSFRFIDFCAGKLFYYGSDGFLSAN 650
651 KSIGTFFNGCYETLYNGCTAIVGHTKSFIYNASNAVYNFFSTIFAGLLNF 700
701 STSSQNSILSLLKSFGTGITNIFYNFIYAPIAGVFNFAGDNYMYFFNEVA 750
751 AVFGKVYNSVVSVLKTVINWILFLIAYPFSLCTRAWIRISQYAPEDVVQV 800
801 IPIPQAITPTPDVERIVEEPLRKVTDVEDEELVIIPAPAPKPIPVPAPTP 850
851 APVIIHQTNVVETVDKDAIIKEVTEKLRAELSAQFQQELSAKFEQNYNTI 900
901 IEQLKMENTNIQYDKNHLEAIIRQMIYEYDTDKTGKVDYALESSGGAVVS 950
951 TRCSETYKSYTRLEKFWDIPIYYFHYSPRVVIQRNSKSLFPGECWCFKES 1000
1001 RGYIAVELSHFIDVSSISYEHIGSEVAPEGNRSSAPKGVLVWAYKQIDDL 1050
1051 NSRVLIGDYTYDLDGPPLQFFLAKHKPDFPVKFVELEVTSNYGAPFTCLY 1100
1101 RLRVHGKVVQV 1111
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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