 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q00383 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MIFKSFILGNLVSLCMKIININSVVVVGLYYGFLTTFSIGPSYLFLLRAQ 50
51 VMEEGTENKVSATTGFITGQLVMFISIYYAPLHLALGRPHTITVLALPYL 100
101 FFNFFWNNHKHFFDYGSTPRNSMRNFSIQCVFLNNLILQLFNYFILQSSM 150
151 LARLVNIYMFRCNNNILFLTSSFVGWLIGHILLIKWLGLVLVWIRQNNYI 200
201 RSNKYLVSEFINYMARIFSILLFITCVYYLGRIPSPFFSTKLTETLKKEQ 250
251 QKVEDEDIETVNQMPPLGLEKREQEQEGSNIKDFYYFSEEMVNLNNNKID 300
301 IDETEKKLVNGKKDELYPRLKITETGYKKIPIFEESSIININENPYNSRF 350
351 KILNKKFEKKNLLIKEKLFVNLIFDKNRWNRPFRYIKNTHFEGATRNEMS 400
401 QFFFNICENDGKERISFTYLSSLSFFLEMIKKKINSHKLEKALTNKLSNF 450
451 WLYTNKKSIKNFTDEFINRIEALDKKFISYNILETRTRLCNDNYTKEYLS 500
501 KKYDPLLNRSYQKTIYINLSTPILKKTPTINLIDNFGINRIHGILLSYTD 550
551 CQEFEQKIKRFYKKQLSTEIVDLLTFISKVVIELGPDSLNCKIFSDVKII 600
601 KKFLLYLLTQIVTNVNDPKIIKKSTRIKKICKKVLRWSYKLITELEQQSG 650
651 EYYENIPIDHQIRSRKSKSVVIFTTTKDNTDSNLYTNDQADTDEVLIHYS 700
701 QQSDFQRGIIKGSMRSQRRKIFNLNLFQANVHSLIFLDRIKKKPIFFFDI 750
751 SESIKLIFRNWACIGKGESFKILKYTEKQTKREEKKEKNKKREKARIEIA 800
801 EAWDTIPLAQVIRSCVLLIQSTFRKYIILPSLIIAKNIIHILLFQLPEWA 850
851 EDFREWDKEVHIKCTYNGVPLSKTNFSINWLTEGIQIKILFPFYLKTWNK 900
901 SKLVSSQKNLIKKQKSNFCFLTVWGMEAKLPFDSPRKQLSLFNFINFVKF 950
951 GKLNKKFIKLSKETIKWVKKKKKDYLISNQIIHESLSKNPSLSWINYSFK 1000
1001 EMDLADQTSKILNQTERISKDKKQVTIKIFNILCENKINYNTKKRLEKWK 1050
1051 ILIRKSERIIIKLLFFFKFFIERIYTNFFLSSINILKINKEIFIKLIKKI 1100
1101 IDKSIFNNERKQELINTKNKNPILFISKLLYNISNSKKNSYTFYGLDLYY 1150
1151 VSQAYVFYKLSQVLVSNSYKFRADLQHLINYNYKRIPPFFKPEKKDFLKT 1200
1201 QGVVDLNFGDKKFKNYAINKWKFWLREHYKYSLSQKKRPILISEKCRTVH 1250
1251 WRNIASKKNNRYDLLSYKILNSKNKTKTEFFLNKSSSQKNNKQEIFYISK 1300
1301 NIPLKIFMRNIHIHKKNYFNNNIKNIVRFGTLYMEYIEKMANRKYFDWKI 1350
1351 INFLSKKKIYIETFIIINTNKNQNNKIIFNKDLYYFIISEKNISNSKKGF 1400
1401 FYWMKMNAKILNHPIFNLENWFFPEFILLYNAYKIKPWFIKNKLLFINFT 1450
1451 INKNSSKTINEKKGPTGREDLGSVLILSQKKDIEESYERSEKEKRKKQYK 1500
1501 NKTEAELDFFLKRCFLFQLRFSDTLNKRMINNIKIYCLLLRLIDPRKIII 1550
1551 SSIHKREINLDIIPIRKNLILTELIKNGVLIIETIRFSRKYGQFSMYQTI 1600
1601 GISLINKNKQQTNKKYQDQIYFSKKKKFNLLFPENILSFRRRKKLRILIC 1650
1651 LNSKNVNDIDINPIFWNEKKIKKNIQVSYDNKNIDVYKKKLIKLKLFIWP 1700
1701 NYRLEDLACMNRYWFYTNNGSRFNMLRVHLYPRLKFYE 1738
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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