 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6UX02 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MEDGKRERWPTLMERLCSDGFAFPQYPIKPYHLKRIHRAVLHGNLEKLKY 50
51 LLLTYYDANKRDRKERTALHLACATGQPEMVHLLVSRRCELNLCDREDRT 100
101 PLIKAVQLRQEACATLLLQNGANPNITDFFGRTALHYAVYNEDTSMIEKL 150
151 LSHGTNIEECSKCEYQPLLFAVSRRKVKMVEFLLKKKANVNAIDYLGRSA 200
201 LIHAVTLGEKDIVILLLQHNIDVLSRDAFRKIAGDYAIEAKNRVIFDLIY 250
251 EYERKRYEDLPINSNPVSSQKQPALKATSGKEDSISNIATEIKDGQKSGT 300
301 VSSQKQPALKDTSDKDDSVSNTATEIKDEQKSGTVLPAVEQCLNRSLYRP 350
351 DAVAQPVTENEFSLESEIISKLYIPKRKIISPRSIKDVLPPVEEAVDRCL 400
401 YLLDRFAQPVTKDKFALESENISEPYFTNRRTISQQSAENLDAACGIDKT 450
451 ENGNMFEDQNVDKEGKALPATGQKANVSPEQPPLFTHTVKDRDHISTRFL 500
501 GGMDSLTSSEESSERPPLSTLTLKEADPSSKAAMRRKDSPPPGKVSSQKQ 550
551 PAEKATSDDKDSVSNIATEIKEGPISGTVSSQKQPAEKATSDEKDSVSNI 600
601 ATEIKKGQQSGTVSPQKQSAWKVIFKKKVSLLNIATRIMGGGKSGTVSSQ 650
651 KQPASKATSDKTDSALNIATEIKDGLQCGTVSSQKQPALKATTDEEDSVS 700
701 NIATEIKDGEKSGTVSSQKQPALKATTDEEDSVSNIATEIKDGEKSGTVS 750
751 SQKQPALKATTDEKDSVSNIATEIKDGEKSGTVSSQKPPALTATSDEEGS 800
801 VLSIARENKDGEKSRTVSSRKKPALKATSDEKDSFSNITRGKKDGEISRK 850
851 VSSQKPPTLKGTSDEEDSVLGIARENKDGEKSRTVSSEKPPGLKASSAEK 900
901 DSVLNIARGKKDGEKTKRVSSRKKPSLEATSDEKDSFSNITREKKDGEIS 950
951 RKVSSQKPPALKGTSDEEDSVLGIARENKDGEKSRTVSSEKPPGLKATSD 1000
1001 EKDSVLNIARGKKDGEKTRTVSSQKPPTLKATSDEEDSVLSIARENKDGE 1050
1051 KSRTVSSEKPSGLKATSAEKDSVLNIARGKKYGEKTKRVSSRKKPALKAT 1100
1101 SDEKDSVLYIAREKKDGEKSRTVSSPKQPALKAICDKEDSVPNMATEKKD 1150
1151 EQISGTVSCQKQPALKATSDKKDSVSNIPTEIKDGQQSGTVSSQKQPAWK 1200
1201 ATSVKKDSVSNIATEIKDGQIRGTVSPQKQSAQKVIFKKKVSLLNIATRI 1250
1251 TGGWKSGTEYPENLPTLKATIENKNSVLNTATKMKDVQTSTPAEQDLEMA 1300
1301 SEGEQKRLEEYENNQPQVKNQIHSRDDLDDIIQSSQTVSEDGDSLCCNCK 1350
1351 NVILLIDQHEMKCKDCVHLLKIKNTFCLWKRLIKLKDNHCEQLRVKIRKL 1400
1401 KNKASVLQKRISEKEEIKSQLKHEILELEKELCSLRFAIQQEKKKRRNVE 1450
1451 EVHQKVREKLRITEEQYRIEADVTKPIKPALKSAEVELKTGGNNSNQVSE 1500
1501 TDEKEDLLHENRLMQDEIARLRLEKDTIKNQNLEKKYLKDFEIVKRKHED 1550
1551 LQKALKRNGETLAKTIACYSGQLAALTDENTTLRSKLEKQRESRQRLETE 1600
1601 MQSYHCRLNAARCDHDQSHSSKRDQELAFQGTVDKCRHLQENLNSHVLIL 1650
1651 SLQLSKAESKSRVLKTELHYTGEALKEKALVFEHVQSELKQKQSQMKDIE 1700
1701 KMYKSGYNTMEKCIEKQERFCQLKKQNMLLQQQLDDARNKADNQEKAILN 1750
1751 IQARCDARVQNLQAECRKHRLLLEEDNKMLVNELNHSKEKECQYEKEKAE 1800
1801 REVAVRQLQQKRDDVLNKGSATKALLDASSRHCTYLENGMQDSRKKLDQM 1850
1851 RSQFQEIQDQLTATIRCTKEMEGDTQKLEVEHVMMRKIIKKQDDQIERLE 1900
1901 KILQHSSLMLQVFES 1915
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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