 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q53TS8 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MEPPQETNRPFSTLDNRSGQVQVLSATPLLQRNPYSSPDIMHIKGSEASS 50
51 VPYALNQGTTALPKNKNQEGTGHRLLNMLRKTLKESDSEELEITQETPNL 100
101 VPFGDVVGCLGIHIKNCRHFMPKISLQHYANLFIRISINKAVKCTKMCSL 150
151 LSKNDEKNTVIKFDEVKYFSVQVPRRYDDKRNNILLELIQYDNREKRAFL 200
201 LGSVQIHLYEVIQKGCFIEEVQVLHGNIFVCRLEVEFMFSYGNFGYGFSH 250
251 QLKPLQKITEPSMFMNLAPPPERTDPVTKVITPQTVEYPAFLSPDLNVTV 300
301 GTPAVQSSNQPSVVRLEKLQQQPRERLEKMKKEYRNLNTWIDKANYLESI 350
351 LMPKLEHKDSEETNIDEASENTKSNHPEEELENIVGVDIPLVNEEAETTA 400
401 NELLDNDSEKGLTIPTLNQSDQDNSTADASKNDESTPSPTEVHSLCTISN 450
451 QETIKAGRIPPLGERQSESMPDRKMKNVFFPLEVKLKDNYPSILKADSSL 500
501 SEVAFSPKEYNSPSFRPEYIEFKPKFQFQKFNKNGFDPFLRNINKMSVRK 550
551 RKDQDIYKYRNILGAEVIEHEDQDPPYPAQSKTAGPANTTWAHDPNIFTT 600
601 KMLETENKLAPDPTINTIKGLDTKNSLKENLPNVSLPSIKGESSRAGNVQ 650
651 ANTCHLSKSLNFTPHIEYLKQSMILKSILSENLQDLSDKLFSKPEVSMNS 700
701 EAREKSSSPLLSIHDKSSSSMEDNVLEKKQDLNNWLSEKDILNSKTTLSQ 750
751 IIKNIPADSFSEGSQIIENIPADSLLEGGQVIKNIPEYSLSEGGQIIKNI 800
801 PADSFLESGPGQSPEVEEHVSKKHFEADERDFPIKKNSSTKKKHLISEVP 850
851 NSKSGSSGTVHDYIMRQIFTAPIFSELEIEVKEPSETPMNLENQLPTPWK 900
901 RSLSSHILFHEENADEIELPQPRSATSQIIQAFPIDTLLESGIIKVIELD 950
951 KEHHKSSLLGTGITSPKGNLKDSQEYYSEIRSETEPLSEQSIPIIPKDTT 1000
1001 SVSRAEFIQEDQNMFPQDSSYYSIANKELYLPRNGQRLCKDKNDLSSTLE 1050
1051 SLTNSLMDKLSESDEIMLKSFLKNIFNVFFKYNHSERRGQPEKELERLIQ 1100
1101 PSFTSDTEHLEELQEDFDKADKLDRKPILSPKLRVFLEELSESEVKHLKS 1150
1151 ELSKQIQHYLVERLSESGHITKEDLPKIYQNLYLMNEKAEQKGPNSFQGK 1200
1201 YSETVKEIMSFVNNFNHHFIDKHLEIKLRSFLKEILQNYFLKNISESSLF 1250
1251 NETASETIYPNISSLRTKSVSISFHELEQDISKGSFGRRFEINMKYPLSK 1300
1301 SLQNYLIALSENELLHLKADLSKHLQSLFIEKLSKSGLMTKKQLEGINQH 1350
1351 INLLNSSSIPLKYIKTHLPFRDDCHFVEKHSEKQNKYSRIVQQTTLQTVS 1400
1401 EDKLREAELIREKEKKYFPLQNLKGNSSLIKEQKSYYTKEEAKTPSLIKV 1450
1451 QPSSNENIQASPLSKSSEILTDILLKKLRKEHVFTQLPQAENSVHKTEIQ 1500
1501 DPYSWGGKSKITQSKAWCEKTLKMKSLDRKEHVNIYKWTVQEKPEAVLTS 1550
1551 YPRIPNARMPREDEYLNRITFPSWQSSTLTHFNTETGEKSKLEDQYCQTL 1600
1601 KGNNNNNKKHLVTFAQYKKEIQTLYIKPDEICSEKCAKFPEIQSFQYKVV 1650
1651 EDEKNLKPHLFPELFKIEDLKPKVRKERDRVAQPKKSFNKIVRILPTTLP 1700
1701 TTRIHLKKSVPRTLLHWTARRTIHDCSDKFEDLHDMTSFTHLKKVKSRSR 1750
1751 LLGKSSDDIHNHARHSARPYTAPEVNKQRESYSGKFTSRRMVSSGLVHIN 1800
1801 DKTSDYEMHKMRPKKIKRGY 1820
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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