 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q496M8 from www.uniprot.org...
The NucPred score for your sequence is 0.70 (see score help below)
1 MECCRRATPGTLLLFLAFLLLSSRTARSEEDRDGLWDAWGPWSECSRTCG 50
51 GGASYSLRRCLSSKSCEGRNIRYRTCSNVDCPPEAGDFRAQQCSAHNDVK 100
101 HHGQFYEWLPVSNDPDNPCSLKCQAKGTTLVVELAPKVLDGTRCYTESLD 150
151 MCISGLCQIVGCDHQLGSTVKEDNCGVCNGDGSTCRLVRGQYKSQLSATK 200
201 SDDTVVAIPYGSRHIRLVLKGPDHLYLETKTLQGTKGENSLSSTGTFLVD 250
251 NSSVDFQKFPDKEILRMAGPLTADFIVKIRNSGSADSTVQFIFYQPIIHR 300
301 WRETDFFPCSATCGGGYQLTSAECYDLRSNRVVADQYCHYYPENIKPKPK 350
351 LQECNLDPCPASDGYKQIMPYDLYHPLPRWEATPWTACSSSCGGGIQSRA 400
401 VSCVEEDIQGHVTSVEEWKCMYTPKMPIAQPCNIFDCPKWLAQEWSPCTV 450
451 TCGQGLRYRVVLCIDHRGMHTGGCSPKTKPHIKEECIVPTPCYKPKEKLP 500
501 VEAKLPWFKQAQELEEGAAVSEEPSFIPEAWSACTVTCGVGTQVRIVRCQ 550
551 VLLSFSQSVADLPIDECEGPKPASQRACYAGPCSGEIPEFNPDETDGLFG 600
601 GLQDFDELYDWEYEGFTKCSESCGGGVQEAVVSCLNKQTREPAEENLCVT 650
651 SRRPPQLLKSCNLDPCPARWEIGKWSPCSLTCGVGLQTRDVFCSHLLSRE 700
701 MNETVILADELCRQPKPSTVQACNRFNCPPAWYPAQWQPCSRTCGGGVQK 750
751 REVLCKQRMADGSFLELPETFCSASKPACQQACKKDDCPSEWLLSDWTEC 800
801 STSCGEGTQTRSAICRKMLKTGLSTVVNSTLCPPLPFSSSIRPCMLATCA 850
851 RPGRPSTKHSPHIAAARKVYIQTRRQRKLHFVVGGFAYLLPKTAVVLRCP 900
901 ARRVRKPLITWEKDGQHLISSTHVTVAPFGYLKIHRLKPSDAGVYTCSAG 950
951 PAREHFVIKLIGGNRKLVARPLSPRSEEEVLAGRKGGPKEALQTHKHQNG 1000
1001 IFSNGSKAEKRGLAANPGSRYDDLVSRLLEQGGWPGELLASWEAQDSAER 1050
1051 NTTSEEDPGAEQVLLHLPFTMVTEQRRLDDILGNLSQQPEELRDLYSKHL 1100
1101 VAQLAQEIFRSHLEHQDTLLKPSERRTSPVTLSPHKHVSGFSSSLRTSST 1150
1151 GDAGGGSRRPHRKPTILRKISAAQQLSASEVVTHLGQTVALASGTLSVLL 1200
1201 HCEAIGHPRPTISWARNGEEVQFSDRILLQPDDSLQILAPVEADVGFYTC 1250
1251 NATNALGYDSVSIAVTLAGKPLVKTSRMTVINTEKPAVTVDIGSTIKTVQ 1300
1301 GVNVTINCQVAGVPEAEVTWFRNKSKLGSPHHLHEGSLLLTNVSSSDQGL 1350
1351 YSCRAANLHGELTESTQLLILDPPQVPTQLEDIRALLAATGPNLPSVLTS 1400
1401 PLGTQLVLDPGNSALLGCPIKGHPVPNITWFHGGQPIVTATGLTHHILAA 1450
1451 GQILQVANLSGGSQGEFSCLAQNEAGVLMQKASLVIQDYWWSVDRLATCS 1500
1501 ASCGNRGVQQPRLRCLLNSTEVNPAHCAGKVRPAVQPIACNRRDCPSRWM 1550
1551 VTSWSACTRSCGGGVQTRRVTCQKLKASGISTPVSNDMCTQVAKRPVDTQ 1600
1601 ACNQQLCVEWAFSSWGQCNGPCIGPHLAVQHRQVFCQTRDGITLPSEQCS 1650
1651 ALPRPVSTQNCWSEACSVHWRVSLWTLCTATCGNYGFQSRRVECVHARTN 1700
1701 KAVPEHLCSWGPRPANWQRCNITPCENMECRDTTRYCEKVKQLKLCQLSQ 1750
1751 FKSRCCGTCGKA 1762
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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