 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q2QL83 from www.uniprot.org...
The NucPred score for your sequence is 0.69 (see score help below)
1 MQRSPLEKASVLSKLFFSWTRPILRKGYRQRLELSDIYQIPSADSADNLS 50
51 EKLEREWDRELASKKNPKLINALRRCFFWRFMFYGILLYLGEVTKAVQPL 100
101 LLGRIIASYDPDNKVERSIAIYLGIGLCLLFIVRMLLLHPAIFGLHHIGM 150
151 QMRIAMFSLIYKKILKLSSRVLDKISIGQLVSLLSNNLNKFDEGLALAHF 200
201 VWIAPLQVMLLMGLLWELLQASAFCGLGFLIVLALFQSGLGRMMMKYRDQ 250
251 RAGKINERLVITSEMIENIQSVKAYCWEEAMEKMIENLRQTELKLTRKAA 300
301 YVRYFNSSAFFFSGFFVVFLSVLPYALIKGIILRKIFTTISFCIVLRMAV 350
351 TRQFPWAVQTWYDSLGAINKIQDFLQKQEYKTLEYNLTTTEVVMENVTAF 400
401 WEEGFGELFEKAKQNSDNRKISNGDNSLFFSNLALLGTPVLKDISFKIER 450
451 GQLLAVAGSTGAGKTSLLMMIMGELEPSEGKIKHSGRISFCSQFSWIMPG 500
501 TIKENIIFGVSYDEYRYRSVIKACQLEEDIAKFAEKDNIVLGEGGITLSG 550
551 GQRARISLARAVYKDADLYLLDSPFGYLDVLTEKEIFESCVCKLMANKTR 600
601 ILVTSKMEHLKKADKILILHEGSSYFYGTFSELQNLRPDFSSKLMGYDSF 650
651 DQFSAERRNSILTETLRRFSLEGDAAVSWNETKKQSFKQTGEIGEKRKNS 700
701 ILNSINSLRKFSVVQKTPLQMSGIEEDPDEPSERRLSLVPDSEQGEAILP 750
751 RSNVINTGPTFQGRRRQSVLNLMTHSVNQGQNIHRINAASTRKMSIAPPA 800
801 NLTEMDIYSRRLSQESSLEISEEINEEDLKECFFDDAENIPAVTTWNTYL 850
851 RYITVHKSLIFVLIWCLVIFLAEVAVSLVLLWLLGNAPAYNKGNSTISAN 900
901 SSYAVIITSTSAYYVFYIYVGVADTLLALGFFRGLPLVHTLITVSKILHH 950
951 KMLHSVLQAPMSTLNALKAGGILNRFSKDIAILDDLLPLTIFDFIQLLLI 1000
1001 VIGAVAVVSVLQPYIFLATVPVIVTFIILRAYFLHTSQQLKQLESEGRSP 1050
1051 IFTHLVTSLKGLWTLRAFGRQPYFETLFHKALNLHTANWFLYLSTLRWFQ 1100
1101 MRIEMVFVIFFIVVTFISILTTGEGEGQVGIILTLAMNIMGTLQWAVNSS 1150
1151 IDVDSLMRSVSRVFKFIDMPTEEGKSTRSIKPSKDCHLSKVMVFENPHVK 1200
1201 KDDIWPSGGQMTVKDLTARYLDGGNAILENISFSISPGQRVGLLGRTGSG 1250
1251 KSTLLSAFLRLLNTEGEIQIDGVSWDSITLQQWRKAFGVIPQKVFIFSGT 1300
1301 FRKNLDPYEQWSDQEIWKVADEVGLRSVIEQFPGKLDFVLVDGGYVLSHG 1350
1351 HKQLMCLARSVLSKAKILLLDEPSAHLDPITYQIIRRTLKQAFADCTVIL 1400
1401 CEHRIEAMLECQRFLVIEENNVRQYDSIQKLLSEKSLFRQAISPSDRMKL 1450
1451 FPRRNSSKHKSRPPITALKEETEEEVQDTRL 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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