 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9MYL0 from www.uniprot.org...
The NucPred score for your sequence is 0.37 (see score help below)
1 MICQKFCVVLLHWEFICVITAFNLSYPITPWRFKLSCMPPNSTYDYFLLP 50
51 AGLSKNTSNLNGHYETAVEFNSSDTHFSNLSKTTFHCCFRSEQDRNCSLC 100
101 ADNIEGKTFVSTVNSSVFQQMGANWNIQCWLKGDLKLFICYVESLFKNPF 150
151 KNYKHKVHLLYVLPEVLEDSPLVPQKGSFQMVHCNCSVHERCECLVPVPT 200
201 AKLNDTLLMCLKITSGGVIFQSPLMSVQPINMVKPDPPLGLRMEITDDGN 250
251 LKISWSSPPLVPFPLQYEVKYSENSTTVIREADKIVSATSLLVDGILPGS 300
301 SYEVQVRGKRLDGPGIWSDWSTPHVFTTQDVIYFPPKILTSVGSNVSFHC 350
351 IYKNENKIVSSKKIVWWMNLAEKIPQSQYDVVSDHVSKVTFFNLNETKPR 400
401 GKFTYDAVYCCNEHECHHRYAELYVIDVNINISCETDGHLTKMTCRWSTN 450
451 TIQSLAGSTLQLRYRRSSLYCFDIPSIHPISKPKDCYLQSDGFYECVFQP 500
501 IFLLSGYTMWIRINHPLGSLDSPPTCVLPDSVVKPLPPSSVKAEIIKNIG 550
551 LLKISWEKPVFPENNLQFQIRYGLSGKEIQWKMYDVYDAKSKSVSLPVPD 600
601 FCAVYAVQVRCKRSDGLGLWSNWSNPAYTVVMDIKVPMRGPEFWRIINGD 650
651 TMKKEKNVTLLWKPLMKNESLCSVQRYVINHHTSCNGTWSEDVGNHTKFT 700
701 FLWTEQAHTVTVLAINSIGASVANFNLTFSWPMSKVNIVQSLSAYPLNSS 750
751 CVILSWILSPSDYKLMYFIIEWKNLNEDGEIKWLRISSSVKKYYIHDHFI 800
801 PIEKYQFSLYPIFMEGVGKPKIINSFAQDNTEKHQNDAGLYVIVPVIISS 850
851 SILLLGTLLILHQRMKKLFWEDVPNPKNCSWAQGLNFQKPETFEHLFIKH 900
901 TASVTCGPLLLEPETISEDISVDTSWKNKDEMVPTTVVSLLSTTDLEKGS 950
951 VCISDQFNSVNFSEAEGTEVTCEDESQRQPFVKYATLISNSKPSETDEEQ 1000
1001 GLINSSVTKCFSSKNSPLKDSFSNSSWEIEAQAFFILSDQRPNIILPHLT 1050
1051 FSEGLDELLRLEGNFPEENNDEKSIYYLGVTSIKKRESGVLLTDKSRVLC 1100
1101 PFPAPCLFTDIRVLQDSCSHFVENNFNLGTSSKKTFASYMPQFQTCSTQT 1150
1151 HKIMENKMCDLTV 1163
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.