 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13388 from www.uniprot.org...
The NucPred score for your sequence is 0.59 (see score help below)
1 MEFLRGGAALLQLLLVLSISRCCSTDPDRKVCQGTSNQMTMLDNHYLKMK 50
51 KMYSGCNVVLENLEITYTQENQDLSFLQSIQEVGGYVLIAMNEVSTIPLV 100
101 NLRLIRGQNLYEGNFTLLVMSNYQKNPSSPDVYQVGLKQLQLSNLTEILS 150
151 GGVKVSHNPLLCNVETINWWDIVDKTSNPTMNLIPHAFERQCQKCDHGCV 200
201 NGSCWAPGPGHCQKFTKLLCAEQCNRRCRGPKPIDCCNEHCAGGCTGPRA 250
251 TDCLACRDFNDDGTCKDTCPPPKIYDIVSHQVVDNPNIKYTFGAACVKEC 300
301 PSNYVVTEGACVRSCSAGMLEVDENGKRSCKPCDGVCPKVCDGIGIGSLS 350
351 NTIAVNSTNIRSFSNCTKINGDIILNRNSFEGDPHYKIGTMDPEHLWNLT 400
401 TVKEITGYLVIMWWPENMTSLSVFQNLEIIRGRTTFSRGFSFVVVQVRHL 450
451 QWLGLRSLKEVSAGNVILKNTLQLRYANTINWRRLFRSEDQSIEYDARTE 500
501 NQTCNNECSEDGCWGPGPTMCVSCLHVDRGGRCVASCNLLQGEPREAQVD 550
551 GRCVQCHQECLVQTDSLTCYGPGPANCSKSAHFQDGPQCIPRCPHGILGD 600
601 GDTLIWKYADKMGQCQPCHQNCTQGCSGPGLSGCRGDIVSHSSLAVGLVS 650
651 GLLITVIVALLIVVLLRRRRIKRKRTIRCLLQEKELVEPLTPSGQAPNQA 700
701 FLRILKETEFKKDRVLGSGAFGTVYKGLWNPDGENIRIPVAIKVLREATS 750
751 PKVNQEVLDEAYVMASVDHPHVCRLLGICLTSAVQLVTQLMPYGCLLDYV 800
801 RQHQERICGQWLLNWCVQIAKGMNYLEERHLVHRDLAARNVLLKNPNHVK 850
851 ITDFGLSKLLTADEKEYQADGGKVPIKWMALESILQWTYTHQSDVWSYGV 900
901 TVWELMTFGSKPYDGIPAKEIASVLENGERLPQPPICTIEVYMIILKCWM 950
951 IDPSSRPRFRELVGEFSQMARDPSRYLVIQGNLPSLSDRRLFSRLLSSDD 1000
1001 DVVDADEYLLPYKRINRQGSEPCIPPTGHPVRENSITLRNISDPTQNALE 1050
1051 KDLDGHEYVNQPGSETSSRLSDIYNPNYEDLTDGWGPVSLSSQEAETNFS 1100
1101 RPEYLNTNQNSLPLVSSGSMDDPDYQAGYQAAFLPQTGALTGNGMFLPAA 1150
1151 ENLEYLGQGGALYTPVR 1167
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.