 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9TUQ2 from www.uniprot.org...
The NucPred score for your sequence is 0.80 (see score help below)
1 MQRSPLEKASVVSKLFFSWTRPILRKGYRQRLELSDIYQIPSADSADNLS 50
51 EKLEREWDRELASKKNPKLINALRRCFFWRFMFYGILLYLGEVTKAVQPL 100
101 LLGRIIASYDPDNKEERSIAIYLGIGLCLLFIVRTLLLHPAIFGLHHIGM 150
151 QMRIAMFSLIYKKTLKLSSRVLDKISIGQLVSLLSNNLNKFDEGLALAHF 200
201 VWIVPLQVALLMGLIWELLQASAFCGLGFLIVLALFQAGLGRMMMKYRDQ 250
251 RAGKINERLVITSEMIENIQSVKAYCWEEAMEKMIENLRQTELKLTRKAA 300
301 YVRYFNSSAFFFSGFFVVFLSVLPYALIKGIVLRKIFTTISFCIVLRMAV 350
351 TRQFPWAVQTWYDSLGAINKIQDFLQKQEYKTLEYNLTTTEVVMENVTAF 400
401 WEEGFGELFEKAKQNNSNRKTSNDDDSLFFSNFSLLGTPVLKDINFKIER 450
451 GQLLAVAGSTGAGKTSLLMMIMGELEPSEGKIKHSGRISFCSQFSWIMPG 500
501 TIKENIIFGVSYDEYRYRSVINACQLEEDISKFAEKDNIVLGEGGITLSG 550
551 GQRARISLARAVYKDADLYLLDSPFGYLDVLTEKEIFESCVCKLMANKTR 600
601 ILVTSKMEHLKKADKILILHEGSSYFYGTFSELQNLRPDFSSKLMGYDSF 650
651 DQFSAERRNSILTETLRRFSLEGDAPVSWTETKKQSFKQTGEFGEKRKNS 700
701 ILNPINSIRKFSIVQKTPLQMNGIEEDSDEPLERRLSLVPDSEQGEVILP 750
751 RISVISTGPTLQARRRQSVLNLMTHSVNQGQSIHRKTAASTRKVSLAPQA 800
801 NLTELDIYSRRLSQETGLEISEEINEEDLKECFFDDMESIPAVTTWNTYL 850
851 RYITVHKSLIFVLIWCLVIFLAEVAASLVVLWFLGNTPPQDKGNSTYSRN 900
901 NSYAVIITRTSSYYVFYIYVGVADTLLAMGFFRGLPLVHTLITVSKILHH 950
951 KMLHSVLQAPMSTLNTLKAGGILNRFSKDIAILDDLLPLTIFDFIQLLLI 1000
1001 VIGAIAVVAVLQPYIFVATVPVIVAFIMLRAYFLQTSQQLKQLESEGRSP 1050
1051 IFTHLVTSLKGLWTLRAFGRQPYFETLFHKALNLHTANWFLYLSTLRWFQ 1100
1101 MRIEMIFVIFFIAVTFISILTTGEGEGTVGIILTLAMNIMSTLQWAVNSS 1150
1151 IDVDSLMRSVSRVFKFIDMPTEEGKPTRSTKPYKNGQLSKVMVIENSHVK 1200
1201 KDDIWPSGGQMTVKDLTAKYTEGGNPILENISFSISPGQRVGLLGRTGSG 1250
1251 KSTLLSAFLRLLNTEGEIQIDGVSWDSITLQQWRKAFGVIPQKVFIFSGT 1300
1301 FRKNLDPYEQWSDQEIWKVADEVGLRSVIEQFPGKLDFVLVDGGCVLSHG 1350
1351 HKQLMCLARSVLSKAKILLLDEPSAHLDPVTYQIIRRTLKQAFADCTVIL 1400
1401 CEHRIEAMLECQQFLVIEENKVRQYDSIQKLLNERSLFQQAISPSDRVKL 1450
1451 FPHRNSSKCKTQPQIAALKEETEEEVQDTRL 1481
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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