 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P70569 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MTYSELYSRYTRVWIPDPDEVWRSAELTKDYKDGDESLQLRLEDDTILDY 50
51 PIDVQNNQVPFLRNPDILVGENDLTALSHLHEPAVLHNLKVRFLESNHIY 100
101 TYCGIVLVAINPYEQLPIYGQDVIYAYSGQNMGDMDPHIFAVAEEAYKQM 150
151 ARDEKNQSIIVSGESGAGKTVSAKYAMRYFATVGGSASDTNIEEKVLASS 200
201 PIMEAIGNAKTTRNDNSSRFGKYIEIGFDKKYHIIGANMRTYLLEKSRVV 250
251 FQADDERNYHIFYQLCAAASLPEFKELALTCAEDFFYTAHGGNTTIEGVD 300
301 DAEDFEKTRQALTLLGVRESHQISIFKIIASILHLGSVEIQAERDGDSCS 350
351 ISPQDEHLSNFCRLLGIEHSQMEHWLCHRKLVTTSETYVKTMSLQQVVNA 400
401 RNALAKHIYAQLFSWIVEHINKALQTSLKQHSFIGVLDIYGFETFEINSF 450
451 EQFCINYANEKLQQQFNSHVFKLEQEEYMKEQIPWTLIDFYDNQPCIDLI 500
501 EAKLGILDLLDEECKVPKGTDQNWAQKLYERHSNSQHFQKPRMSNTAFIV 550
551 IHFADKVEYLSDGFLEKNRDTVYEEQINILKASKFPLVADLFRDDEDSVP 600
601 ATNTAKSRSSSKINVRSSRPLMKAPNKEHKKSVGYQFRTSLNLLMETLNA 650
651 TTPHYVRCIKPNDEKLPFHFDPKRAVQQLRACGVLETIRISAAGYPSRWT 700
701 YHDFFNRYRVLMKKRELANTTDKKNICKSVLESLIKDPDKFQFGRTKIFF 750
751 RAGQVAYLEKLRADKFREATIMIQKTVRGWLQRVKYRRLRAATLTLQRFC 800
801 RGYLARRLTEHLRRTRAAIVFQKQYRMLKARRAYCRVRRAAVIIQSYTRG 850
851 HVCTQKLPPVLTEHKATIIQKYARGWMARRHFQRQRDAAIVIQCAFRRLK 900
901 ARQALKALKIEARSAEHLKRLNVGMENKVVQLQRKIDDQNKEFKTLSEQL 950
951 SAVTSTHAMEVEKLKKELARYQQNQEADPSLQLQEEVQSLRTELQKAHSE 1000
1001 RRVLEDAHNRENGELRKRVADLEHENALLKDEKEHLNHQILRQSKAESSQ 1050
1051 SSVEENLLIKKELEEERSRYQNLVKEYSQLEQRYENLRDEQQTPGHRKNP 1100
1101 SNQSSLESDSNYPSISTSEIGDTEDALQQVEEIGIEKAAMDMTVFLKLQK 1150
1151 RVRELEQERKKLQVQLEKEQQDSKKVQVEQQNNGLDVDQDADIAYNSLKR 1200
1201 QELESENKKLKNDLNERWKAVADQAMQDNSTHSSPDSYSLLLNQLKLANE 1250
1251 ELEVRKEEVLILRTQIMNADQRRLSGKNMEPNINARTSWPNSEKHVDQED 1300
1301 AIEAYHGVCQTNSQTEDWGYLNEDGELGLAYQGLKQVARLLEAQLQAQNL 1350
1351 KHEEEVEHLKAQVEAMKEEMDKQQQTFCQTLLLSPEAQVEFGVQQEISRL 1400
1401 TNENLDFKELVEKLEKNEKKLKKQLKIYMKKVQDLEAAQALAQSDRRHHE 1450
1451 LTRQVTVQRKEKDFQGMLEYHKEDEALLIRNLVTDLKPQMLSGTVPCLPA 1500
1501 YILYMCIRHADYTNDDLKVHSLLSSTINGIKKVLKKHNEDFEMTSFWLSN 1550
1551 TCRLLHCLKQYSGDEGFMTQNTAKQNEHCLKNFDLTEYRQVLSDLSIQIY 1600
1601 QQLIKIAEGLLQPMIVSAMLENESIQGLSGVRPTGYRKRSSSMVDGENSY 1650
1651 CLEAIIRQMNFFHTVLCDQGLDPEIILQVFKQLFYMINAVTLNNLLLRKD 1700
1701 ACSWSTGMQLRYNISQLEEWLRGKNLQQSGAVQTMEPLIQAAQLLQLKKK 1750
1751 TQEDAEAICSLCTSLSTQQIVKILNLYTPLNGFEERVTVSFIRTIQAQLQ 1800
1801 ERSDPQQLLLDSKHMFPVLFPFNPSALTMDSIHIPACLNLEFLNEV 1846
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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