 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q4WTV7 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MTGAPPYNPQSPTQQPRFPVYSPPNKNRSYYPNNDQYQQHAPQTPPAFAP 50
51 QPSLSRSPHYSHAPSPLPATLPPLNGGAPPPGHHPEPSSQYQTHSSAGTP 100
101 QFSLPRPYSASMMSSNGASSYNHSTASHAHPSARLESLSQSPPKKETEPL 150
151 YPIGGNGAPGYSSSMMREPRPASPPRETKHARAADPMSFASILSGPTEET 200
201 SPIKQPSLPEALPGPATTITPAPPTLAPVPARRRLTPPPVTHALPPTSQL 250
251 KVKEPEPISPAALPRLEKKPSAEKRRRNVEQEPKSAEALPVASTHGAFEP 300
301 TKAARVSNRKTLTERDAEAINKIIAEIDNADKSDVESPGFEVEYGRYMVK 350
351 SKKRALDAEKAEGIRRKRRRHDFLVKLGKTFEKQANAGVDRFRAANEASV 400
401 IAEVQAKEIQDEKERKKDMQRKRRRENTVRLEMQKKLEAERKANKANDAA 450
451 EKAKFLREAERAQRKIKSTKRALEGVTSPEEIGEVTPLAPNLEGGTTSSF 500
501 HIGRSSPSRRKSGRSGTSRPKKSKEQKQAEKDAAEAAYAAMENDEPLPLA 550
551 PKEDPRKETVKKEAKGARSKETTPAPVSAFESKGYNQIYEQIWRDIARKD 600
601 IPKVYRIKTLSLSTRQENLRKTAQLASKQSRKWQERTNKSMKDTQARAKR 650
651 TMREMMSFWKRNEREERDLRRLAEKQEIESAKKAEAEREANRQKRKLNFL 700
701 ISQTELYSHFIGRKIKGAGADSSGDTAVDGSDETIQPGKADHTIDLPPTV 750
751 ADVGAKVTNFEDLDFDAEDETALRQAALANAQNAVKEAQERARAFNAEEN 800
801 PMAALDEGELNFQNPTSLGDIEISQPKMLTAKLKEYQLKGLNWLVNLYEQ 850
851 GINGILADEMGLGKTIQSISVMAYLAEVHNIWGPFLVIAPASTLHNWQQE 900
901 ITKFVPDIKVLPYWGSAKDRKVLRKFWDRKHITYTKESEFHVLVTSYQLV 950
951 VLDSQYFQKVKWQYMILDEAQAIKSSQSSRWKNLLGFHCRNRLLLTGTPI 1000
1001 QNNMQELWALLHFIMPTLFDSHDEFSEWFSKDIESHAQSNTKLNEDQLRR 1050
1051 LHMILKPFMLRRVKKHVQQELGDKVEKDVFCDLTYRQRAYYTNLRNRVSI 1100
1101 MDLIEKAAVGDEADSTTLMNLVMQFRKVCNHPDLFERAETKSPFSVGYFA 1150
1151 ETASFVREGQNVDVRYSTRNLIEYNLPRLLCSPSGRIDMAGPGNEHAGFR 1200
1201 GKYLQHLMNIFTPENIKRSIDEDGAFSFLRFADTSINEAYEQSHLGVFER 1250
1251 AVRRRGQSNRLSHLNVIYDDEEDEKTSKFVLPHSLFNIVQRNDRQAVRNV 1300
1301 TVEGYMRDLMNVSEATFERDGLGVIEPSASPAASAPPITISCSGQVALRE 1350
1351 TQDTFFNVSVRHALFSTPSRQMEQQILEKKLDPAPFSLPPMLPKPISTKG 1400
1401 RYTHIEVPSMRRFVTDSGKLAKLDELLRELKAGGHRVLLYFQMTRMIDLM 1450
1451 EEYLTYRNYKYCRLDGSTKLEDRRDTVADFQQRPEIFVFLLSTRAGGLGI 1500
1501 NLTAADTVIFYDSDWNPTIDSQAMDRAHRLGQTRQVTVYRLITRGTIEER 1550
1551 IRKRALQKEEVQRVVISGGAAGGVDFNTRNRESRTKDIAMWLADDEQAEL 1600
1601 IEQKEKEALDRGEVFGAGKGGKKAAQKRKKDLTLDDMYHEGEGNFDDISA 1650
1651 KPSGAATPVSTADNFGTPSSTPVPKRGRGRGNGKGSSKRAKTTTERLRLI 1700
1701 DGDGGLES 1708
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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