 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9ULV0 from www.uniprot.org...
The NucPred score for your sequence is 0.86 (see score help below)
1 MSVGELYSQCTRVWIPDPDEVWRSAELTKDYKEGDKSLQLRLEDETILEY 50
51 PIDVQRNQLPFLRNPDILVGENDLTALSYLHEPAVLHNLKVRFLESNHIY 100
101 TYCGIVLVAINPYEQLPIYGQDVIYTYSGQNMGDMDPHIFAVAEEAYKQM 150
151 ARDEKNQSIIVSGESGAGKTVSAKYAMRYFATVGGSASETNIEEKVLASS 200
201 PIMEAIGNAKTTRNDNSSRFGKYIQIGFDKRYHIIGANMRTYLLEKSRVV 250
251 FQADDERNYHIFYQLCAAAGLPEFKELALTSAEDFFYTSQGGDTSIEGVD 300
301 DAEDFEKTRQAFTLLGVKESHQMSIFKIIASILHLGSVAIQAERDGDSCS 350
351 ISPQDVYLSNFCRLLGVEHSQMEHWLCHRKLVTTSETYVKTMSLQQVINA 400
401 RNALAKHIYAQLFGWIVEHINKALHTSLKQHSFIGVLDIYGFETFEVNSF 450
451 EQFCINYANEKLQQQFNSHVFKLEQEEYMKEQIPWTLIDFYDNQPCIDLI 500
501 EAKLGILDLLDEECKVPKGTDQNWAQKLYDRHSSSQHFQKPRMSNTAFII 550
551 VHFADKVEYLSDGFLEKNRDTVYEEQINILKASKFPLVADLFHDDKDPVP 600
601 ATTPGKGSSSKISVRSARPPMKVSNKEHKKTVGHQFRTSLHLLMETLNAT 650
651 TPHYVRCIKPNDEKLPFHFDPKRAVQQLRACGVLETIRISAAGYPSRWAY 700
701 HDFFNRYRVLVKKRELANTDKKAICRSVLENLIKDPDKFQFGRTKIFFRA 750
751 GQVAYLEKLRADKFRTATIMIQKTVRGWLQKVKYHRLKGATLTLQRYCRG 800
801 HLARRLAEHLRRIRAAVVLQKHYRMQRARQAYQRVRRAAVVIQAFTRAMF 850
851 VRRTYRQVLMEHKATTIQKHVRGWMARRHFQRLRDAAIVIQCAFRMLKAR 900
901 RELKALRIEARSAEHLKRLNVGMENKVVQLQRKIDEQNKEFKTLSEQLSV 950
951 TTSTYTMEVERLKKELVHYQQSPGEDTSLRLQEEVESLRTELQRAHSERK 1000
1001 ILEDAHSREKDELRKRVADLEQENALLKDEKEQLNNQILCQSKDEFAQNS 1050
1051 VKENLMKKELEEERSRYQNLVKEYSQLEQRYDNLRDEMTIIKQTPGHRRN 1100
1101 PSNQSSLESDSNYPSISTSEIGDTEDALQQVEEIGLEKAAMDMTVFLKLQ 1150
1151 KRVRELEQERKKLQVQLEKREQQDSKKVQAEPPQTDIDLDPNADLAYNSL 1200
1201 KRQELESENKKLKNDLNELRKAVADQATQNNSSHGSPDSYSLLLNQLKLA 1250
1251 HEELEVRKEEVLILRTQIVSADQRRLAGRNAEPNINARSSWPNSEKHVDQ 1300
1301 EDAIEAYHGVCQTNSKTEDWGYLNEDGELGLAYQGLKQVARLLEAQLQAQ 1350
1351 SLEHEEEVEHLKAQLEALKEEMDKQQQTFCQTLLLSPEAQVEFGVQQEIS 1400
1401 RLTNENLDLKELVEKLEKNERKLKKQLKIYMKKAQDLEAAQALAQSERKR 1450
1451 HELNRQVTVQRKEKDFQGMLEYHKEDEALLIRNLVTDLKPQMLSGTVPCL 1500
1501 PAYILYMCIRHADYTNDDLKVHSLLTSTINGIKKVLKKHNDDFEMTSFWL 1550
1551 SNTCRLLHCLKQYSGDEGFMTQNTAKQNEHCLKNFDLTEYRQVLSDLSIQ 1600
1601 IYQQLIKIAEGVLQPMIVSAMLENESIQGLSGVKPTGYRKRSSSMADGDN 1650
1651 SYCLEAIIRQMNAFHTVMCDQGLDPEIILQVFKQLFYMINAVTLNNLLLR 1700
1701 KDVCSWSTGMQLRYNISQLEEWLRGRNLHQSGAVQTMEPLIQAAQLLQLK 1750
1751 KKTQEDAEAICSLCTSLSTQQIVKILNLYTPLNEFEERVTVAFIRTIQAQ 1800
1801 LQERNDPQQLLLDAKHMFPVLFPFNPSSLTMDSIHIPACLNLEFLNEV 1848
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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