 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P07768 from www.uniprot.org...
The NucPred score for your sequence is 0.46 (see score help below)
1 MAKRKFSGLEITLIVLFVIVFIIAIALIAVLATKTPAVEEVNPSSSTPTT 50
51 TSTTTSTSGSVSCPSELNEVVNERINCIPEQSPTQAICAQRNCCWRPWNN 100
101 SDIPWCFFVDNHGYNVEGMTTTSTGLEARLNRKSTPTLFGNDINNVLLTT 150
151 ESQTANRLRFKLTDPNNKRYEVPHQFVTEFAGPAATETLYDVQVTENPFS 200
201 IKVIRKSNNRILFDSSIGPLVYSDQYLQISTRLPSEYMYGFGEHVHKRFR 250
251 HDLYWKTWPIFTRDQHTDDNNNNLYGHQTFFMCIEDTTGKSFGVFLMNSN 300
301 AMEIFIQPTPIVTYRVIGGILDFYIFLGDTPEQVVQQYQELIGRPAMPAY 350
351 WSLGFQLSRWNYNSLDVVKEVVRRNREALIPFDTQVSDIDYMEDKKDFTY 400
401 DRVAYNGLPDFVQDLHDHGQKYVIILDPAISINRRASGEAYESYDRGNAQ 450
451 NVWVNESDGTTPIVGEVWPGDTVYPDFTSPNCIEWWANECNIFHQEVNYD 500
501 GLWIDMNEVSSFVQGSNKGCNDNTLNYPPYIPDIVDKLMYSKTLCMDSVQ 550
551 YWGKQYDVHSLYGYSMAIATERAVERVFPNKRSFILTRSTFAGSGRHAAH 600
601 WLGDNTATWEQMEWSITGMLEFGLFGMPLVGADICGFLAETTEELCRRWM 650
651 QLGAFYPFSRNHNADGFEHQDPAFFGQDSLLVKSSRHYLNIRYTLLPFLY 700
701 TLFYKAHAFGETVARPVLHEFYEDTNSWVEDREFLWGPALLITPVLTQGA 750
751 ETVSAYIPDAVWYDYETGAKRPWRKQRVEMSLPADKIGLHLRGGYIIPIQ 800
801 QPAVTTTASRMNPLGLIIALNDDNTAVGDFFWDDGETKDTVQNDNYILYT 850
851 FAVSNNNLNITCTHELYSEGTTLAFQTIKILGVTETVTQVTVAENNQSMS 900
901 THSNFTYDPSNQVLLIENLNFNLGRNFRVQWDQTFLESEKITCYPDADIA 950
951 TQEKCTQRGCIWDTNTVNPRAPECYFPKTDNPYSVSSTQYSPTGITADLQ 1000
1001 LNPTRTRITLPSEPITNLRVEVKYHKNDMVQFKIFDPQNKRYEVPVPLDI 1050
1051 PATPTSTQENRLYDVEIKENPFGIQIRRRSTGKVIWDSCLPGFAFNDQFI 1100
1101 QISTRLPSEYIYGFGEAEHTAFKRDLNWHTWGMFTRDQPPGYKLNSYGFH 1150
1151 PYYMALEDEGNAHGVLLLNSNAMDVTFMPTPALTYRVIGGILDFYMFLGP 1200
1201 TPEVATQQYHEVIGHPVMPPYWSLGFQLCRYGYRNTSEIIELYEGMVAAD 1250
1251 IPYDVQYTDIDYMERQLDFTIDENFRELPQFVDRIRGEGMRYIIILDPAI 1300
1301 SGNETRPYPAFDRGEAKDVFVKWPNTSDICWAKVWPDLPNITIDESLTED 1350
1351 EAVNASRAHAAFPDFFRNSTAEWWTREILDFYNNYMKFDGLWIDMNEPSS 1400
1401 FVNGTTTNVCRNTELNYPPYFPELTKRTDGLHFRTMCMETEHILSDGSSV 1450
1451 LHYDVHNLYGWSQAKPTYDALQKTTGKRGIVISRSTYPTAGRWAGHWLGD 1500
1501 NYARWDNMDKSIIGMMEFSLFGISYTGADICGFFNDSEYHLCTRWTQLGA 1550
1551 FYPFARNHNIQFTRRQDPVSWNQTFVEMTRNVLNIRYTLLPYFYTQLHEI 1600
1601 HAHGGTVIRPLMHEFFDDRTTWDIFLQFLWGPAFMVTPVLEPYTTVVRGY 1650
1651 VPNARWFDYHTGEDIGIRGQVQDLTLLMNAINLHVRGGHILPCQEPARTT 1700
1701 FLSRQKYMKLIVAADDNHMAQGSLFWDDGDTIDTYERDLYLSVQFNLNKT 1750
1751 TLTSTLLKTGYINKTEIRLGYVHVWGIGNTLINEVNLMYNEINYPLIFNQ 1800
1801 TQAQEILNIDLTAHEVTLDDPIEISWS 1827
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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