 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P37297 from www.uniprot.org...
The NucPred score for your sequence is 0.56 (see score help below)
1 MRFTRGLKASSSLRAKAIGRLTKLSTGAPNDQNSNGTTLDLITHTLPIFY 50
51 STNTSKIYTIPLTLSEWEVLTSLCVAIPTTLDLVETMLKEIIAPYFLETP 100
101 RQRISDVLSSKFKLEQMRNPIELLTFQLTKFMIQACEQYPVLYENIGGII 150
151 STYFERVLKIFTIKQSGLLSLVGFINAFIQFPNSTELTKFTWKKLAKLVL 200
201 RGSFLNEVDKILNSSATFTNDSIVQYYDAGNELSSAYLLELISRLQVSLI 250
251 SHLLNTSHVGANLSEFLLNQQYQFYKFDQEVADENDDTKCIDDFFFNVRS 300
301 NKQFFTDMCKISLQFCSESHILDLSTDNRARFSFDTRAHYLQTLCLIPFI 350
351 EDTESELFESFTNVVSESIDKFFLSDVVTPSLIKAIVASASLLNFFTEKL 400
401 SLTLIRMFPLLVASPHITTETVNDVAKIFTTGLYPLNEDAIVSTIYSMNN 450
451 LLAVSEDGSPVPVLRERQLTITSGKNIEKDYFPLRNSSASLDGTGALLGN 500
501 TTVGQLSSHDVNSGATMTYHASLISNCVAATTTIASYYNTQSITALTISI 550
551 LTQKVNSMSKELDGVILNSLARLAPNTSLTEFSLLLKFFKSRTVIATKID 600
601 DSALLKNIIKAKCVISKELLARHFSSDLYFMYLHDLLDSIIASGEVERLE 650
651 HHRPQTEISRVADQIATYLEPLAALLPVPGDTPLDINKDEVTTNKFRNAW 700
701 FNFVIHGYHLGGPIVKRNFSFLLTIAYNSPPLASEFPANNKELSLEMNTI 750
751 LRRGSSNENIKQQKQQITEYFNTNIVQYRTTSSSKIMFLAAAVLLETIRC 800
801 EAGDCSKTLLYFSDPSILSGSIEKCIAVLSVSMIRKYARLIQKGNDAIFN 850
851 SKMIAQQLNNLLLCLSHREPTLQDAAFHACEIFIRSIPSSLCHHLSLYTL 900
901 LDMLTALFDSILDSEAHKFEPRYEFKLKHSKTTILVPSSSSWRATTLSRL 950
951 HKSAKEWVRILLNRSNQDTKILLQSYISDLGEYSRLNSVEFGVSFAMDMA 1000
1001 GLILPADKELSRLTYYGPEKPNTISGFISLHSWRSKYLFDTAITSSPEDI 1050
1051 KRQIGISTQNIRKNLTLGNKIITKDVTDFLDMATALLILGNGAPASLIYD 1100
1101 IVHIPFEVFTSASLKIATNVWLTIITEKPEVAHLLLVEVCYCWMRSIDDN 1150
1151 IGLYSRDHDLKGEEYQKMEYSPYDKAGINRDAKNASQAMQPHLHVIKFFA 1200
1201 SHFEGTLFQSDFLLKIFTKCALYGIKNLYKASLHPFARMIRHELLLFATL 1250
1251 VLNASYKQGSKYMGRLSQEITNGALSWFKRPVAWPFGSNELKIKADLSVT 1300
1301 RDLFLQLNKLSSLMSRHCGKDYKILNYFLASEIQQIQTWLTPTEKIEGAD 1350
1351 SNELTSDIVEATFAKDPTLAINLLQRCYSKKAEDVLVGLVAKHALMCVGS 1400
1401 PSALDLFIKGSHLSSKKDLHATLYWAPVSPLKSINLFLPEWQGNSFILQF 1450
1451 SIYSLESQDVNLAFFYVPQIVQCLRYDKTGYVERLILDTAKISVLFSHQI 1500
1501 IWNMLANCYKDDEGIQEDEIKPTLDRIRERMVSSFSQSHRDFYEREFEFF 1550
1551 DEVTGISGKLKPYIKKSKAEKKHKIDEEMSKIEVKPDVYLPSNPDGVVID 1600
1601 IDRKSGKPLQSHAKAPFMATFKIKKDVKDPLTGKNKEVEKWQAAIFKVGD 1650
1651 DCRQDVLALQLISLFRTIWSSIGLDVYVFPYRVTATAPGCGVIDVLPNSV 1700
1701 SRDMLGREAVNGLYEYFTSKFGNESTIEFQNARNNFVKSLAGYSVISYLL 1750
1751 QFKDRHNGNIMYDDQGHCLHIDFGFIFDIVPGGIKFEAVPFKLTKEMVKV 1800
1801 MGGSPQTPAYLDFEELCIKAYLAARPHVEAIIECVNPMLGSGLPCFKGHK 1850
1851 TIRNLRARFQPQKTDHEAALYMKALIRKSYESIFTKGYDEFQRLTNGIPY 1900
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.) |
Go back to the NucPred Home Page.