 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9SZ67 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MSEKEELPLTLTSIGAATATSDYHQRVGSSGEGISSSSSDVDPRFMQNSP 50
51 TGLMISQSSSMCTVPPGMAATPPISSGSGLSQQLNNSSSSKLCQVEGCQK 100
101 GARDASGRCISHGGGRRCQKPDCQKGAEGKTVYCKAHGGGRRCEYLGCTK 150
151 GAEGSTDFCIAHGGGRRCNHEDCTRSAWGRTEFCVKHGGGARCKTYGCGK 200
201 SASGPLPFCRAHGGGKKCSHEDCTGFARGRSGLCLMHGGGKRCQRENCTK 250
251 SAEGLSGLCISHGGGRRCQSIGCTKGAKGSKMFCKACITKRPLTIDGGGN 300
301 MGGVTTGDALNYLKAVKDKFEDSEKYDTFLEVLNDCKHQGVDTSGVIARL 350
351 KDLFKGHDDLLLGFNTYLSKEYQITILPEDDFPIDFLDKVEGPYEMTYQQ 400
401 AQTVQANANMQPQTEYPSSSAVQSFSSGQPQIPTSAPDSSLLAKSNTSGI 450
451 TIIEHMSQQPLNVDKQVNDGYNWQKYGQKKVKGSKFPLSYYKCTYLGCPS 500
501 KRKVERSLDGQVAEIVYKDRHNHEPPNQGKDGSTTYLSGSSTHINCMSSE 550
551 LTASQFSSNKTKIEQQEAASLATTIEYMSEASDNEEDSNGETSEGEKDED 600
601 EPEPKRRITEVQVSELADASDRTVREPRVIFQTTSEVDNLDDGYRWRKYG 650
651 QKVVKGNPYPRFSSSKDYDVVIRYGRADISNEDFISHLRASLCRRGISVY 700
701 EKFNEVDALPKCRVLIIVLTSTYVPSNLLNILEHQHTEDRVVYPIFYRLS 750
751 PYDFVCNSKNYERFYLQDEPKKWQAALKEITQMPGYTLTDKSESELIDEI 800
801 VRDALKVLCSADKVNMIGMDMQVEEILSLLCIESLDVRSIGIWGTVGIGK 850
851 TTIAEEIFRKISVQYETCVVLKDLHKEVEVKGHDAVRENFLSEVLEVEPH 900
901 VIRISDIKTSFLRSRLQRKRILVILDDVNDYRDVDTFLGTLNYFGPGSRI 950
951 IMTSRNRRVFVLCKIDHVYEVKPLDIPKSLLLLDRGTCQIVLSPEVYKTL 1000
1001 SLELVKFSNGNPQVLQFLSSIDREWNKLSQEVKTTSPIYIPGIFEKSCCG 1050
1051 LDDNERGIFLDIACFFNRIDKDNVAMLLDGCGFSAHVGFRGLVDKSLLTI 1100
1101 SQHNLVDMLSFIQATGREIVRQESADRPGDRSRLWNADYIRHVFINDTGT 1150
1151 SAIEGIFLDMLNLKFDANPNVFEKMCNLRLLKLYCSKAEEKHGVSFPQGL 1200
1201 EYLPSKLRLLHWEYYPLSSLPKSFNPENLVELNLPSSCAKKLWKGKKARF 1250
1251 CTTNSSLEKLKKMRLSYSDQLTKIPRLSSATNLEHIDLEGCNSLLSLSQS 1300
1301 ISYLKKLVFLNLKGCSKLENIPSMVDLESLEVLNLSGCSKLGNFPEISPN 1350
1351 VKELYMGGTMIQEIPSSIKNLVLLEKLDLENSRHLKNLPTSIYKLKHLET 1400
1401 LNLSGCISLERFPDSSRRMKCLRFLDLSRTDIKELPSSISYLTALDELLF 1450
1451 VDSRRNSPVVTNPNANSTELMPSESSKLEILGTPADNEVVVGGTVEKTRG 1500
1501 IERTPTILVKSREYLIPDDVVAVGGDIKGLRPPVLQLQPAMKLSHIPRGS 1550
1551 TWDFVTHFAPPETVAPPSSSSEAREEEVETEETGAMFIPLGDKETCSFTV 1600
1601 NKGDSSRTISNTSPIYASEGSFITCWQKGQLLGRGSLGSVYEGISADGDF 1650
1651 FAFKEVSLLDQGSQAHEWIQQVEGGIALLSQLQHQNIVRYRGTTKDESNL 1700
1701 YIFLELVTQGSLRKLYQRNQLGDSVVSLYTRQILDGLKYLHDKGFIHRNI 1750
1751 KCANVLVDANGTVKLADFGLAKVMSLWRTPYWNWMAPEVILNPKDYDGYG 1800
1801 TPADIWSLGCTVLEMLTGQIPYSDLEIGTALYNIGTGKLPKIPDILSLDA 1850
1851 RDFILTCLKVNPEERPTAAELLNHPFVNMPLPSSGSGSVSSLLRG 1895
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.) |
Go back to the NucPred Home Page.