 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13819 from www.uniprot.org...
The NucPred score for your sequence is 0.78 (see score help below)
1 MKIIFFLCSFLFFIINTQCVTHESYQELVKKLEALEDAVLTGYSLFQKEK 50
51 MVLNEGTSGTAVTTSTPGSSGSVTSGGSVASVASVASGGSGGSVASGGSG 100
101 NSRRTNPSDNSSDSNTKTYADLKHRVQNYLFTIKELKYPELFDLTNHMLT 150
151 LSKNVDGFKYLIDGYEEINELLYKLNFYYDLLRAKLNDACANSYCQIPFN 200
201 LKIRANELDVLKKIVFGYRKPLDNIKDNVGKMEDYIKKNKTTIANINELI 250
251 EGSKKTIDQNKNADNEEGKKKLYQAQYNLFIYNKQLQEAHNLISVLEKRI 300
301 DTLKKNENIKKLLEDIDKIKTDAENPTTGSKPNPLPENKKKEVEGHEEKI 350
351 KEIAKTIKFNIDSLFTDPLELEYYLREKNKKVDVTPKSQDPTKSVQIPKV 400
401 PYPNGIVYPLPLTDIHNSLAADNDKNSYGDLMNPDTKEKINEKIITDNKE 450
451 RKIFINNIKKQIDLEEKNINHTKEQNKKLLEDYEKSKKDYEELLEKFYEM 500
501 KFNNNFDKDVVDKIFSARYTYNVEKQRYNNKFSSSNNSVYNVQKLKKALS 550
551 YLEDYSLRKGISEKDFNHYYTLKTGLEADIKKLTEEIKSSENKILEKNFK 600
601 GLTHSANASLEVSDIVKLQVQKVLLIKKIEDLRKIELFLKNAQLKDSIHV 650
651 PNIYKPQNKPEPYYLIVLKKEVDKLKEFIPKVKDMLKKEQAVLSSITQPL 700
701 VAASETTEDGGHSTHTLSQSGETEVTEETEVTEETVGHTTTVTITLPPKE 750
751 ESAPKEVKVVENSIEHKSNDNSQALTKTVYLKKLDEFLTKSYICHKYILV 800
801 SNSSMDQKLLEVYNLTPEEENELKSCDPLDLLFNIQNNIPAMYSLYDSMN 850
851 IDLQHLFFELYQKEMIYYLHKLKEENHIKKLLEEQKQITGTSSTSSPGNT 900
901 TVNTAQSATHSNSQNQQSNASSTNTQNGVAVSSGPAVVEESHDPLTVLSI 950
951 SNDLKGIVSLLNLGNKTKVPNPLTISTTEMEKFYENILKNNDTYFNDDIK 1000
1001 QFVKSNSKVITGLTETQKNALNDEIKKLKDTLQLSFDLYNKYKLKLDRLF 1050
1051 NKKKELGQDKMQIKKLTLLKEQLESKLNSLNNPHNVLQNFSVFFNKKKEA 1100
1101 EIAETENTLENTKILLKHYKGLVKYYNGESSPLKTLSEVSIQTEDNYANL 1150
1151 EKFRALSKIDGKLNDNLHLGKKKLSFLSSGLHHLITELKEVIKNKNYTGN 1200
1201 SPSENNKKVNEALKSYENFLPEAKVTTVVTPPQPDVTPSPLSVRVSGSSG 1250
1251 STKEETQIPTSGSLLTELQQVVQLQNYDEEDDSLVVLPIFGESEDNDEYL 1300
1301 DQVVTGEAISVTMDNILSGFENEYDVIYLKPLAGVYRSLKKQIEKNIITF 1350
1351 NLNLNDILNSRLKKRKYFLDVLESDLMQFKHISSNEYIIEDSFKLLNSEQ 1400
1401 KNTLLKSYKYIKESVENDIKFAQEGISYYEKVLAKYKDDLESIKKVIKEE 1450
1451 KEKFPSSPPTTPPSPAKTDEQKKESKFLPFLTNIETLYNNLVNKIDDYLI 1500
1501 NLKAKINDCNVEKDEAHVKITKLSDLKAIDDKIDLFKNTNDFEAIKKLIN 1550
1551 DDTKKDMLGKLLSTGLVQNFPNTIISKLIEGKFQDMLNISQHQCVKKQCP 1600
1601 ENSGCFRHLDEREECKCLLNYKQEGDKCVENPNPTCNENNGGCDADATCT 1650
1651 EEDSGSSRKKITCECTKPDSYPLFDGIFCSSSNFLGISFLLILMLILYSF 1700
1701 I 1701
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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