 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9EQW7 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MSDTKVKVAVRVRPMNRRELELNTKCVVEMEGNQTVLHPPPSNTKQGERK 50
51 PPKVFAFDYCFWSMDESNTTKYAGQEVVFKCLGEGILEKAFQGYNACIFA 100
101 YGQTGSGKSFSMMGHAEQLGLIPRLCCALFQRIALEQNESQTFKVEVSYM 150
151 EIYNEKVRDLLDPKGSRQSLKVREHKVLGPYVDGLSQLAVTSFEDIESLM 200
201 SEGNKSRTVAATNMNEESSRSHAVFNIIITQTLYDLQSGNSGEKVSKVSL 250
251 VDLAGSERVSKTGAAGERLKEGSNINKSLTTLGLVISSLADQAAGKGKNK 300
301 FVPYRDSVLTWLLKDNLGGNSQTSMIATISPAADNYEETLSTLRYADRAK 350
351 RIVNHAVVNEDPNAKVIRELREEVEKLREQLSKAEAMKPPELKEKLEESE 400
401 KLIKELTVTWEEKLRKTEAIAQERQRQLESMGISLETSGIKVGDDKCYLV 450
451 NLNADPALNELLVYYLKDHTRVGADTSQDIQLFGIGIQPEHCEIDIAADG 500
501 DITLTPKENARSCVNGTLVCNTTQLWHGDRILWGNNHFFRINLPKRKRRD 550
551 WLKDFERETSSAEHDLDAASEASSEPDYNYEFAQMEVIMKTLNSNDPVQN 600
601 VVQVLEKQYLEEKRTALEEQRLMYERELEQLRQQLSPERQPPSSASDRLA 650
651 YSSQTAQQKVTQWAEERDELFRQSLAKLREQLVKANTLVREANFLAEEMS 700
701 KLTDYQVTLQIPAANLSANRKRGAIVSEPAIQARRKGKGTQVWTIEKLEN 750
751 KLIDMRDLYQEWKENVPEAKRLYGKRGDPFYEAQENHNLIGVANVFLECL 800
801 FCDVKLQYAVPIISQQGEVAGRLHVEVTRITGTIPERMAEDDSSENSSES 850
851 GSLEVVDSSGEVIHRVKKLTCRVIIKEATGLPISLSNFVFCQYTFWDQCE 900
901 STVAAPVVDPDVPSPQSKDAQYTVTFSHCKDYVVTVTEEFLEFISDGALA 950
951 IEVWGHRCAGNGSPIWEVDSLHAKTRTLHDRWNEVTRRIEVWISILELNE 1000
1001 LGDYAAVELHQAKDVNTGGVFQLRQGHSRRVQVTVKPVQHSGTLPLMVEA 1050
1051 ILSVSIGCVTARSTKLQRGLDSYQEEDLNCVRERWSDALIKRREYLDEQI 1100
1101 KKVSNKKEKTEDDMEREARLVEQWVGLTEERNAVLVPAPGSGIPGAPADW 1150
1151 VPPPGMETHIPVLFLDLNADDLSANEQLVGPHASGVNSILPKEHGSQFFY 1200
1201 LPIIKHSDDEVSATASWDSSVHDSLHLNRVTPQNERIYLIVKTTVQLSHP 1250
1251 AAMELVLRKRIAANIYNKQSFTQSLKRRISLINICYSCGVTYEIVSNIPK 1300
1301 ATEEIEDRETLALLAARSENEGTLDGETYIEKYTRGVLQVENILSLERLR 1350
1351 QAVTVKEALSTKARHIRRSLSTPNVHNVSSSRPDLSGFDEDDKGWPENQL 1400
1401 DVSDYSSSYQDVACYGTLPRDSPRRSKEGCPSENPHALTVSPFKAFSPQP 1450
1451 PKFFKPLMPVKEEHKKRLALEARPLLSQEDSEEEENELEALSRKLMLTQP 1500
1501 YVPVEFADFSVYNASLENREWSSSKADLTDSRALEKAVSRSPTTSSLTSG 1550
1551 YFSHSASNATLSDMAVPSSDSSDQLAVSTKEVECAEPPGPSLAPDVRRAS 1600
1601 NQELTEVGRGSGKDETIAVPLEENSALPKGTPSPQSIPEESSRMPCRTAS 1650
1651 CSELDVGPSKDGHQAREFCPGEVTIEHTTNILEDHSFTEFMGVSDGKDFD 1700
1701 GLADCSVGEPSRRRALTNETDHKGIPERPPDADRLHPKIENDQEATATR 1749
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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