 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P08111 from www.uniprot.org...
The NucPred score for your sequence is 0.58 (see score help below)
1 MLKFIRGKGQQPSADRHRLQKDLFAYRKTAQHGFPHKPSALAYDPVLKLM 50
51 AIGTQTGALKVFGQPGVELYGQHTLLNNSASELNVQLLEWVYGTGRILSL 100
101 TAANQLILWEPVGATLLPIKTLPFDGKLKKVSSLCCSLSKDLLWIGTEGG 150
151 NIYQLDLHTFTIKEPVIYHDVVLEQVPPAYKLNPGAIESIRQLPNSPSKL 200
201 LVAYNRGLCVLWDFESASVQRAYIAPGHGQSVGLTVNFEGSEFTWYHADG 250
251 SYATWSIDNPEPPSNVNYVPYGPDPCKSINRLYKGKRRSNDVIVFSGGMP 300
301 RSAYGDHNCVSVHASDGHKVCLDFTSKVIDFFVTFENNRDVAEVLVVLLE 350
351 EELCAYDLTDPNICAIKAPYLHSVHASAVTCNYLASEVVQSVYESILRAG 400
401 DEQDIDYSNISWPITGGTLPDNLEESVEEDATKLYEILLTGHEDGSVKFW 450
451 DCTGVLLKPIYNFKTSSIFGSESDFRDDAAADMSAEQVDEGEPPFRKSGL 500
501 FDPYSDDPRLAVKKIAFCPKTGQLIVGGTAGQIVIADFIDLPEKVSLKYI 550
551 SMNLVSDRDGFVWKGHDQLNVRSNLLDGEAIPTTERGVNISGVLQVLPPA 600
601 SITCMALEASWGLVSGGTAHGLVLFDFKNFVPVFHRCTLNPNDLTGAGEQ 650
651 LSRRKSFKKSLRESFRKLRKGRSTRTNQSNQVPTTLEARPVERQIEARCA 700
701 DDGLGSMVRCLLFAKTYVTNVNITSPTLWSATNASTVSVFLLHLPPAQTA 750
751 ATAVPSASGNAPPHMPRRISAQLAKEIQLKHRAPVVGISIFDQAGSPVDQ 800
801 LNAGENGSPPHRVLIASEEQFKVFSLPQLKPINKYKLTANEGARIRRIHF 850
851 GSFSCRISPETLQSMHGCSPTKSTRSHGDGEADPNISGSLAVSRGDVYNE 900
901 TALICLTNMGDIMVLSVPELKRQLNAAAVRREDINGVSSLCFTNSGEALY 950
951 MMSSSELQRIALATSRVVQPTGVVPVEPLENEESVLEENDAENNKETYAC 1000
1001 DEVVNTYEIKNPSGISICTRPAEENVGRNSVQQVNGVNISNSPNQANETI 1050
1051 SSSIGDITVDSVRDHLNMTTTTLCSINTEETIGRLSVLSTQTNKASTTVN 1100
1101 MSEIPNINISNLEDLESKRNTTETSTSSVVIKSIITNISHEKTNGDNKIG 1150
1151 TPKTAPEESQF 1161
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.