 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P53705 from www.uniprot.org...
The NucPred score for your sequence is 0.83 (see score help below)
1 MQTSISTTTIEDHLHHYSPEESQKLLSRESSINTDLFKHENESVDLLLKE 50
51 MNSTPSKLLPIDKHSHLQLQPQSSSASIFNSPTKPLNFPRTNSKPSLDPN 100
101 SSSDTYTSEQDQEKGKEEKKDTAFQTSFDRNFDLDNSIDIQQTIQHQQQQ 150
151 PQQQQQLPQTDNNLIDEFSFQTPMTSTLDLTKQNPTVDKINENHAPTYIN 200
201 TSPNKSIMKKATPKASPKKVAFTATNPEIHHYPDNRVEEEDQSQQKEDSV 250
251 EPPSIQHQWKDPSQFNYSDEDTNASVPPTPPLHTTKPTFAQLLNKNNEVN 300
301 SEPEALTDMKLKHENFSNLSLDEKVNLYLSPTNNNNSKNVSDMDSHLQNL 350
351 QDASKNKTNENIHNLSFALKAPKNDIENPLNSLTNADISLRSSGSSQSSL 400
401 QSLRDDNRVLESTPGSPKKVNPGLSLNDGIKGFSDEVVESLLPRDLSRDK 450
451 LETTKENDAPEHNNENFIDAKSTNTNKGQLLVSSDDHLDSFDRSYNHTEQ 500
501 SILNLLNSASQSQISLNALEKQKQIQEQEQTQAAEPEEETSFSDNIKVKQ 550
551 EPKSNLEFVKVTIKKEPVSATEIKAPKREFSSRILRIKNEDEIAEPADIH 600
601 PKKENEANSHVEDTDALLKKALNDDEESDTTQNSTKMSIRFHIDSDWKLE 650
651 DSNDGDREDNDDISRFEKSDILNDVSQTSDIIGDKYGNSSSEITTKTLAP 700
701 PRSDNNDKENSKSFEDPANNESSQQQLEVPHTKEDDSILANSSNIAPPEE 750
751 LTLPVVEANDYSSFNDVTKTFDAYSSFEESLSREHETDSKPINFISIWHK 800
801 QEKQKKHQIHKVPTKQIIASYQQYKNEQESRVTSDKVKIPNAIQSKKFKE 850
851 VNVMSRRVVSPDMDDLNVSQFLPELSEDSGFKDLNFANYSNNTNRPRSFT 900
901 PLSTKNVLSNIDNDPNVVEPPEPKSYAEIRNARRLSANKAAPNQAPPLPP 950
951 QRQPSSTRSNSNKRVSRFRVPTFEIRRTSSALAPCDMYNDIFDDFGAGSK 1000
1001 PTIKAEGMKTLPSMDKDDVKRILNAKKGVTQDEYINAKLVDQKPKKNSIV 1050
1051 TDPEDRYEELQQTASIHNATIDSSIYGRPDSISTDMLPYLSDELKKPPTA 1100
1101 LLSADRLFMEQEVHPLRSNSVLVHPGAGAATNSSMLPEPDFELINSPTRN 1150
1151 VSNNSDNVAISGNASTISFNQLDMNFDDQATIGQKIQEQPASKSANTVRG 1200
1201 DDDGLASAPETPRTPTKKESISSKPAKLSSASPRKSPIKIGSPVRVIKKN 1250
1251 GSIAGIEPIPKATHKPKKSFQGNEISNHKVRDGGISPSSGSEHQQHNPSM 1300
1301 VSVPSQYTDATSTVPDENKDVQHKPREKQKQKHHHRHHHHKQKTDIPGVV 1350
1351 DDEIPDVGLQERGKLFFRVLGIKNINLPDINTHKGRFTLTLDNGVHCVTT 1400
1401 PEYNMDDHNVAIGKEFELTVADSLEFILTLKASYEKPRGTLVEVTEKKVV 1450
1451 KSRNRLSRLFGSKDIITTTKFVPTEVKDTWANKFAPDGSFARCYIDLQQF 1500
1501 EDQITGKALQFDLNCFNEWETMSNGNQPMKRGKPYKIAQLEVKMLYVPRS 1550
1551 DPREILPTSIRSAYESINELNNEQNNYFEGYLHQEGGDCPIFKKRFFKLM 1600
1601 GTSLLAHSEISHKTRAKINLSKVVDLIYVDKENIDRSNHRNFSDVLLLDH 1650
1651 AFKIKFANGELIDFCAPNKHEMKIWIQNLQEIIYRNRFRRQPWVNLMLQQ 1700
1701 QQQQQSSQQ 1709
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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