 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q14203 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MAQSKRHVYSRTPSGSRMSAEASARPLRVGSRVEVIGKGHRGTVAYVGAT 50
51 LFATGKWVGVILDEAKGKNDGTVQGRKYFTCDEGHGIFVRQSQIQVFEDG 100
101 ADTTSPETPDSSASKVLKREGTDTTAKTSKLRGLKPKKAPTARKTTTRRP 150
151 KPTRPASTGVAGASSSLGPSGSASAGELSSSEPSTPAQTPLAAPIIPTPV 200
201 LTSPGAVPPLPSPSKEEEGLRAQVRDLEEKLETLRLKRAEDKAKLKELEK 250
251 HKIQLEQVQEWKSKMQEQQADLQRRLKEARKEAKEALEAKERYMEEMADT 300
301 ADAIEMATLDKEMAEERAESLQQEVEALKERVDELTTDLEILKAEIEEKG 350
351 SDGAASSYQLKQLEEQNARLKDALVRMRDLSSSEKQEHVKLQKLMEKKNQ 400
401 ELEVVRQQRERLQEELSQAESTIDELKEQVDAALGAEEMVEMLTDRNLNL 450
451 EEKVRELRETVGDLEAMNEMNDELQENARETELELREQLDMAGARVREAQ 500
501 KRVEAAQETVADYQQTIKKYRQLTAHLQDVNRELTNQQEASVERQQQPPP 550
551 ETFDFKIKFAETKAHAKAIEMELRQMEVAQANRHMSLLTAFMPDSFLRPG 600
601 GDHDCVLVLLLMPRLICKAELIRKQAQEKFELSENCSERPGLRGAAGEQL 650
651 SFAAGLVYSLSLLQATLHRYEHALSQCSVDVYKKVGSLYPEMSAHERSLD 700
701 FLIELLHKDQLDETVNVEPLTKAIKYYQHLYSIHLAEQPEDCTMQLADHI 750
751 KFTQSALDCMSVEVGRLRAFLQGGQEATDIALLLRDLETSCSDIRQFCKK 800
801 IRRRMPGTDAPGIPAALAFGPQVSDTLLDCRKHLTWVVAVLQEVAAAAAQ 850
851 LIAPLAENEGLLVAALEELAFKASEQIYGTPSSSPYECLRQSCNILISTM 900
901 NKLATAMQEGEYDAERPPSKPPPVELRAAALRAEITDAEGLGLKLEDRET 950
951 VIKELKKSLKIKGEELSEANVRLSLLEKKLDSAAKDADERIEKVQTRLEE 1000
1001 TQALLRKKEKEFEETMDALQADIDQLEAEKAELKQRLNSQSKRTIEGLRG 1050
1051 PPPSGIATLVSGIAGEEQQRGAIPGQAPGSVPGPGLVKDSPLLLQQISAM 1100
1101 RLHISQLQHENSILKGAQMKASLASLPPLHVAKLSHEGPGSELPAGALYR 1150
1151 KTSQLLETLNQLSTHTHVVDITRTSPAAKSPSAQLMEQVAQLKSLSDTVE 1200
1201 KLKDEVLKETVSQRPGATVPTDFATFPSSAFLRAKEEQQDDTVYMGKVTF 1250
1251 SCAAGFGQRHRLVLTQEQLHQLHSRLIS 1278
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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