 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q04205 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MDFGSVMNQAATPCSPAVNYELPSPGQSITKQVDTPDATRSPRGGQAHRK 50
51 ASRSMSVTAAMESSCELDLVYITERIIAVSYPSTAEEQSFRSNLREVAHM 100
101 LKSKHGDNYVLFNLSERRHDISKLHPKVLDFGWPDLHTPALEKICSICKA 150
151 MDTWLNAAAHNVVVLHNKGNRGRLGVVVAAYMHYSNISASADQALDRFAM 200
201 KRFYEDKVVPVGQPSQKRYIHYFSGLLSGSIKMNNKPLFLHHVIMHGIPN 250
251 FESKGGCRPFLKIYQAMQPVYTSGIYNVQGDSQTGICITIEPGLLLKGDI 300
301 LLKCYHKKFRSPTRDVIFRVQFHTCAVHDLDIVFGKEDLDEAFRDERFPE 350
351 YGKVEFVFSYGPEKIQGMEHLENGPSVSVDYNTSDPLIRWDSYENFNIQR 400
401 EDSTEGTWAEPALPGKHLEKEVGHTQGPLDGSLYAKVKKKDSLHGSIGAV 450
451 NAARLPLSAAPNHVEHTLSVSSDSGNSTASTKTDRTDEPGAPGAPTGHAV 500
501 LSPEEKRELDRLLVGFGLESAPPMHNHAPGPAPARLPAGPGRHVVPAQVH 550
551 VNGAGTPLLAERETDILDDELPNQDGHSVGSLGTLSSLDGTTTASEAGFH 600
601 EAPRVGSLSSLPNGPASYNGAEKMLKEGLYEAEPLSNGAYPYSNQNTLMG 650
651 HHLRDPLAHLRPSASAQEHLAGYPQRQPASTSPAWLQPPVPQPYLYGYDL 700
701 PSAHRSQSFPAVGTAKYEANLALPQAPARSTSSREAVQRGLNSWQQQGGS 750
751 RPPSQLHDGGLESHSPSLSSCSPQPSPLQPMPPHSHSMPEFPRAPSRREI 800
801 EQSIEALDVLMLDLAPSVHKSQSVPSAATRQDKPAAMLSSLSAQPLSGHY 850
851 AQPTPQVVQPRSFGTSVGTDPLAKAYSPGPLVPAARSTAEPDYTVHEYRE 900
901 TYTPYSYQPVPEPRSYGSAPASILPLSASYSPAGSQQLLVSSPPSPTAPA 950
951 QSQLPHKGLESYEDLSRSGEEPLNLEGLVAHRVAGVQSREKSPEESTVPA 1000
1001 RRRTPSDSHYEKSSPEPGSPRSPTVLSPEVVSTIAANPGGRPKEPHLHSY 1050
1051 KEAFEEMESASPSSLTSGGVRSPPGLAKTPLSALGLKPHNPADILLHPVG 1100
1101 ELEGEAGADSEEEPRSYVESVARTATTGRAGNLPAAQPVGLEVPARNGAF 1150
1151 GNSFTVPSPVSTSSPIHSVDGASLRSYPSEGSPHGTVTPPHAVAETAYRS 1200
1201 PMVSQTPSAHSSYQTSSPSSFQAGTLGSPYASPDYPDGRAGFQPDPQARQ 1250
1251 QPQVSVVGVHALPGSPRTLHRTVATNTPPSPGFGRRAANPAVASVPGSPG 1300
1301 LGRHTVSPHAPPGSPSLARHQMAAVPPGSPMYGYSSPEERRPTLSRQSSA 1350
1351 SGYQPPSTPSFPVSPAYYPGTSTPHSSSPDSAAYRQGSPTPQPALPEKRR 1400
1401 MSAGERSNSLPNYATVNGKASSPLSSGMSSPSSGSAVAFSHTLPDFSKFS 1450
1451 MPDISPETRANVKFVQDTSKYWYKPDISREQAIALLKDREPGAFIIRDSH 1500
1501 SFRGAYGLAMKVASPPPTVMQQNKKGDITNELVRHFLIETSPRGVKLKGC 1550
1551 PNEPNFGCLSALVYQHSIMPLALPCKLVIPDRDPMEEKKDAASTTNSATD 1600
1601 LLKQGAACNVLFINSVEMESLTGPQAISKAVAETLVADPTPTATIVHFKV 1650
1651 SAQGITLTDNQRKLFFRRHYPLNTVTFCDLDPQERKWTKTDGSGPAKLFG 1700
1701 FVARKQGSTTDNVCHLFAELDPDQPAAAIVNFVSRVMLGSGQKR 1744
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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