 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P12222 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MIFQSFLLGNLVSLCMKIINSVVVVGLYYGFLTTFSIGPSYLFLLRALVM 50
51 EEGTEKKVSATTGFITGQLMMFISIYYAPLHLALGRPHTITVLALPYLLF 100
101 HFFWNNHKHFFDYGSTTRNSMRNLSIQCVFLNNLIFQLFNHFILPSSMLA 150
151 RLVNIYLFRCNSKILFVTSGFVGWLIGHILFMKWLGLVLVWIRQNHSIRS 200
201 NKYIRSNKYLVLELRNSMARIFSILLFITCVYYLGRIPSPILTKKLKEAS 250
251 KTEERVESEEERDVEIETASEMKGTKQEQEGSTEEDPYPSPSLFSEERWD 300
301 PDKIDETEEIRVNGKDKIKDKFHSHLTETGYNNINTSNSPIYDYEDSYLN 350
351 NNNTGNTEIFKLQLLDKKNENKDLFWFQQPLVSLLFDYNRWNRPFRYIKN 400
401 NRFEQAIRTEMSQYFFNTCKSDGKQRISFTYPPSLSTFWKMIKRRIPLLS 450
451 LQKTLPNELDNQWISTNKEKSNNLNKEFLNRLEVLDKESFSLDILETRTR 500
501 LCNDDTKKEYVPKMYDPLLNGPYRGTIKKKFSPSIINNTSLENLKERVRI 550
551 NRIHTIFLPNTDYQELEQKVDTVAKKPLSTEIDEFLTLINEFGNEPKSSL 600
601 NLKDLSLFSDQEQGRVNSEKRTKFVKFVFNAIAPNGTTSEKKSIGIKEIS 650
651 KKIPRWSHKLITELEQQSGDYQEGVPLDHQIRSRKAKRVVIFTANNQNND 700
701 PDTKDTDTADQDQTKEVALIRYSQQPDFRRGIIKGSMRAQRRKTVIWKLF 750
751 QANVHSPLFLDRITPPFLFSFDISGLIKPIFRNWSGKEGEFKILESREEQ 800
801 TKREEKKEKDKKGENKRKEKARIEIAEAWDTIPFAQIIRGYMLITQSILR 850
851 KYIVLPSLIIAKNLGRMLVLQLPEWSEDLQEWNREMHIKCTYNGVQLSET 900
901 EFPKNWLKDGIQIKILFPFCLKPWHISKLYSSRGELMKKKKQKDDFCFLT 950
951 VWGMEAELPFGSPRKRPSFFEPIFKELEKKIGKFKKKYFITLKVFKGKIK 1000
1001 LFRRISKETKKWLIKSSLFIKKMKKELSKVNPIVLFRLKEIDESNETKKE 1050
1051 KDSLMSNQIINESFSQIESGNWPNSSLIESKMKDLTDRTSTIKNQIERIT 1100
1101 KEKKKVTPEIDISPNKTNNIKKFESPKKIFQILKRRNTRLIWKFHYFLKL 1150
1151 FIQRLYIDLFLSIINIPRINTQLFLESTNKLIDKYISNNEINQEKINNQK 1200
1201 KIHFISTIKKSLYNISKKNSHIFFDLSYLSQAYVFYKLSQPQVINLSKLR 1250
1251 SVLQYNRTSFFLKTKIKDYFRTLGIFHSELKHKKLQSYRINQWKNWLRRH 1300
1301 YQYDLSQIRWSRLMPQKWRNRVNQGCMAQNRNLNKWNSYEKDQLIHYKKE 1350
1351 NDSELYSLANQKDNFQKCYRYDLLAYKSINYEKKNDSFISRLPFQVNKNL 1400
1401 EISSNSNTSKHNLFDMLGNLHINNYLRKGNILYIERNLDRKYFDWKIIHF 1450
1451 SLRQKEDIEAWVKIDTNSNPNTKIGINNYQIIDKIDKKGFFYLTIHQNPE 1500
1501 NNQKNSKKAFFDWMGMNEKILNRPILNLEFWFFPEFVPLYNVYKIKPWII 1550
1551 PSKLLLLNLNTNENVSQNKNINKNQKQNFFLRSNKKIKNRIQEAKEPASQ 1600
1601 GEKERGSDIENKGNLGPVLSKHQNALKKDYAESDTKKGKKKKQYKSNTEA 1650
1651 ELDLFLKRYLLFQLRWNDALNQRMIENIKVYCLLLRLINPSKIAISSIQR 1700
1701 REMSLDIMLIQKNLTLTELMKKGILIIEPIRLSVKNNGQFIMYQTIGISL 1750
1751 VHKSKHQTNQRYPEQRYVDKKNFDEFILQPQTQRINTDKNHFDLLVPENI 1800
1801 LWSRRRRELRIRSLFNSLNWNGIDRNSVFCNENNVKNWSQFLDERKPLYK 1850
1851 EKNELIKLKFFLWPNYRLEDLACMNRYWFDTNNGSRFSILRIHMYPQLKI 1900
1901 N 1901
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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