 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9Y6D6 from www.uniprot.org...
The NucPred score for your sequence is 0.70 (see score help below)
1 MYEGKKTKNMFLTRALEKILADKEVKKAHHSQLRKACEVALEEIKAETEK 50
51 QSPPHGEAKAGSSTLPPVKSKTNFIEADKYFLPFELACQSKCPRIVSTSL 100
101 DCLQKLIAYGHLTGNAPDSTTPGKKLIDRIIETICGCFQGPQTDEGVQLQ 150
151 IIKALLTAVTSQHIEIHEGTVLQAVRTCYNIYLASKNLINQTTAKATLTQ 200
201 MLNVIFARMENQALQEAKQMEKERHRQHHHLLQSPVSHHEPESPQLRYLP 250
251 PQTVDHISQEHEGDLDLHTNDVDKSLQDDTEPENGSDISSAENEQTEADQ 300
301 ATAAETLSKNEVLYDGENHDCEEKPQDIVQNIVEEMVNIVVGDMGEGTTI 350
351 NASADGNIGTIEDGSDSENIQANGIPGTPISVAYTPSLPDDRLSVSSNDT 400
401 QESGNSSGPSPGAKFSHILQKDAFLVFRSLCKLSMKPLSDGPPDPKSHEL 450
451 RSKILSLQLLLSILQNAGPIFRTNEMFINAIKQYLCVALSKNGVSSVPEV 500
501 FELSLSIFLTLLSNFKTHLKMQIEVFFKEIFLYILETSTSSFDHKWMVIQ 550
551 TLTRICADAQSVVDIYVNYDCDLNAANIFERLVNDLSKIAQGRGSQELGM 600
601 SNVQELSLRKKGLECLVSILKCMVEWSKDQYVNPNSQTTLGQEKPSEQEM 650
651 SEIKHPETINRYGSLNSLESTSSSGIGSYSTQMSGTDNPEQFEVLKQQKE 700
701 IIEQGIDLFNKKPKRGIQYLQEQGMLGTTPEDIAQFLHQEERLDSTQVGE 750
751 FLGDNDKFNKEVMYAYVDQHDFSGKDFVSALRMFLEGFRLPGEAQKIDRL 800
801 MEKFAARYLECNQGQTLFASADTAYVLAYSIIMLTTDLHSPQVKNKMTKE 850
851 QYIKMNRGINDSKDLPEEYLSAIYNEIAGKKISMKETKELTIPTKSSKQN 900
901 VASEKQRRLLYNLEMEQMAKTAKALMEAVSHVQAPFTSATHLEHVRPMFK 950
951 LAWTPFLAAFSVGLQDCDDTEVASLCLEGIRCAIRIACIFSIQLERDAYV 1000
1001 QALARFTLLTVSSGITEMKQKNIDTIKTLITVAHTDGNYLGNSWHEILKC 1050
1051 ISQLELAQLIGTGVKPRYISGTVRGREGSLTGTKDQAPDEFVGLGLVGGN 1100
1101 VDWKQIASIQESIGETSSQSVVVAVDRIFTGSTRLDGNAIVDFVRWLCAV 1150
1151 SMDELLSTTHPRMFSLQKIVEISYYNMGRIRLQWSRIWEVIGDHFNKVGC 1200
1201 NPNEDVAIFAVDSLRQLSMKFLEKGELANFRFQKDFLRPFEHIMKRNRSP 1250
1251 TIRDMVVRCIAQMVNSQAANIRSGWKNIFSVFHLAASDQDESIVELAFQT 1300
1301 TGHIVTLVFEKHFPATIDSFQDAVKCLSEFACNAAFPDTSMEAIRLIRHC 1350
1351 AKYVSDRPQAFKEYTSDDMNVAPEDRVWVRGWFPILFELSCIINRCKLDV 1400
1401 RTRGLTVMFEIMKTYGHTYEKHWWQDLFRIVFRIFDNMKLPEQQTEKAEW 1450
1451 MTTTCNHALYAICDVFTQYLEVLSDVLLDDIFAQLYWCVQQDNEQLARSG 1500
1501 TNCLENVVILNGEKFTLEIWDKTCNCTLDIFKTTIPHALLTWRPNSGETA 1550
1551 PPPPSPVSEKPLDTISQKSVDIHDSIQPRSVDNRPQAPLVSASAVNEEVS 1600
1601 KIKSTAKFPEQKLFAALLIKCVVQLELIQTIDNIVFFPATSKKEDAENLA 1650
1651 AAQRDAVDFDVRVDTQDQGMYRFLTSQQLFKLLDCLLESHRFAKAFNSNN 1700
1701 EQRTALWKAGFKGKSKPNLLKQETSSLACGLRILFRMYMDESRVSAWEEV 1750
1751 QQRLLNVCSEALSYFLTLTSESHREAWTNLLLLFLTKVLKISDNRFKAHA 1800
1801 SFYYPLLCEIMQFDLIPELRAVLRRFFLRIGVVFQISQPPEQELGINKQ 1849
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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