 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O94986 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MSLDFGSVALPVQNEDEEYDEEDYEREKELQQLLTDLPHDMLDDDLSSPE 50
51 LQYSDCSEDGTDGQPHHPEQLEMSWNEQMLPKSQSVNGYNEIQSLYAGEK 100
101 CGNVWEENRSKTEDRHPVYHPEEGGDEGGSGYSPPSKCEQTDLYHLPENF 150
151 RPYTNGQKQEFNNQATNVIKFSDPQWNHFQGPSCQGLEPYNKVTYKPYQS 200
201 SAQNNGSPAQEITGSDTFEGLQQQFLGANENSAENMQIIQLQVLNKAKER 250
251 QLENLIEKLNESERQIRYLNHQLVIIKDEKDGLTLSLRESQKLFQNGKER 300
301 EIQLEAQIKALETQIQALKVNEEQMIKKSRTTEMALESLKQQLVDLHHSE 350
351 SLQRAREQHESIVMGLTKKYEEQVLSLQKNLDATVTALKEQEDICSRLKD 400
401 HVKQLERNQEAIKLEKTEIINKLTRSLEESQKQCAHLLQSGSVQEVAQLQ 450
451 FQLQQAQKAHAMSANMNKALQEELTELKDEISLYESAAKLGIHPSDSEGE 500
501 LNIELTESYVDLGIKKVNWKKSKVTSIVQEEDPNEELSKDEFILKLKAEV 550
551 QRLLGSNSMKRHLVSQLQNDLKDCHKKIEDLHQVKKDEKSIEVETKTDTS 600
601 EKPKNQLWPESSTSDVVRDDILLLKNEIQVLQQQNQELKETEGKLRNTNQ 650
651 DLCNQMRQMVQDFDHDKQEAVDRCERTYQQHHEAMKTQIRESLLAKHALE 700
701 KQQLFEAYERTHLQLRSELDKLNKEVTAVQECYLEVCREKDNLELTLRKT 750
751 TEKEQQTQEKIKEKLIQQLEKEWQSKLDQTIKAMKKKTLDCGSQTDQVTT 800
801 SDVISKKEMAIMIEEQKCTIQQNLEQEKDIAIKGAMKKLEIELELKHCEN 850
851 ITKQVEIAVQNAHQRWLGELPELAEYQALVKAEQKKWEEQHEVSVNKRIS 900
901 FAVSEAKEKWKSELENMRKNILPGKELEEKIHSLQKELELKNEEVPVVIR 950
951 AELAKARSEWNKEKQEEIHRIQEQNEQDYRQFLDDHRNKINEVLAAAKED 1000
1001 FMKQKTELLLQKETELQTCLDQSRREWTMQEAKRIQLEIYQYEEDILTVL 1050
1051 GVLLSDTQKEHISDSEDKQLLEIMSTCSSKWMSVQYFEKLKGCIQKAFQD 1100
1101 TLPLLVENADPEWKKRNMAELSKDSASQGTGQGDPGPAAGHHAQPLALQA 1150
1151 TEAEADKKKVLEIKDLCCGHCFQELEKAKQECQDLKGKLEKCCRHLQHLE 1200
1201 RKHKAVVEKIGEENNKVVEELIEENNDMKNKLEELQTLCKTPPRSLSAGA 1250
1251 IENACLPCSGGALEELRGQYIKAVKKIKCDMLRYIQESKERAAEMVKAEV 1300
1301 LRERQETARKMRKYYLICLQQILQDDGKEGAEKKIMNAASKLATMAKLLE 1350
1351 TPISSKSQSKTTQSALPLTSEMLIAVKKSKRNDVNQKIPCCIESKSNSVN 1400
1401 TITRTLCEQAPKRRAACNLQRLLENSEHQSIKHVGSKETHLEFQFGDGSC 1450
1451 KHLNSLPRNVSPEFVPCEGEGGFGLHKKKDLLSDNGSESLPHSAAYPFLG 1500
1501 TLGNKPSPRCTPGPSESGCMHITFRDSNERLGLKVYKCNPLMESENAASE 1550
1551 KSQGLDVQEPPVKDGGDLSDCLGWPSSSATLSFDSREASFVHGRPQGTLE 1600
1601 IPSESVKSKQFSPSGYLSDTEESNMICQTMKCQRYQTPYLSEETTYLEPG 1650
1651 KISVNCGHPSRHKADRLKSDFKKLSSTLPSSVCQQPSRKLIVPLSSQQDS 1700
1701 GFDSPFVNLD 1710
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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