 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8C0T5 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MTSLKRSQTERPVTADRASVVSTDGAPKVHTDDFYMRRFRSQNGSLGSSV 50
51 MAAVGPPRSEGPHHITSTPGVPKMGVRARIADWPPRKENVKESSRSSQEI 100
101 ETSSCLESLSSKGSPVSQGSSVSLNSNDSAMLKSIQNTLKNKTGPAESMD 150
151 SRFLMPEAYPSSPRKALRRIRQRSNSDITISELDVDSFDECISPTYKSGP 200
201 SLHREYGSTSSIDKQGTSGDSFFDLLKGYKDDRSDRGPTPTKLSDFLITG 250
251 GGKGSGFSLDVIDGPISQRENLRLFKEREKPLKRRSKSETGDSSIFRKLR 300
301 NAKGEELGKSSDLEDNRSEDSVRPWTCPKCFAHYDVQSILFDLNEAIMNR 350
351 HNVIKRRNTTTGASAAAVASLVSGPLSHSASFSSPMGSTEDLNSKGSLGM 400
401 DQGDDKSNELVMSCPYFRNEIGGEGERKISLSKSNSGSFSGCESTSFESA 450
451 LSSHCTNAGVAVLEVPKESLMLHLDRVKRYTVEHVDLGAYYYRKFFYQKE 500
501 HWNYFGADENLGPVAVSIRREKPEDMKENGSPYNYRIIFRTSELMTLRGS 550
551 VLEDAIPSTAKHSTARGLPLKEVLEHVIPELNVQCLRLAFNTPKVTEQLM 600
601 KLDEQGLNYQQKVGIMYCKAGQSTEEEMYNNESAGPAFEEFLQLLGERVR 650
651 LKGFEKYRAQLDTKTDSTGTHSLYTTYKDYEIMFHVSTMLPYTPNNKQQL 700
701 LRKRHIGNDIVTIVFQEPGAQPFSPKNIRSHFQHVFVIVRAHNPCTESVC 750
751 YSVAVTRSRDVPSFGPPIPKGVTFPKSNVFRDFLLAKVINAENAAHKSEK 800
801 FRAMATRTRQEYLKDLAEKNVTNTPIDPSGKFPFISLASKKKEKSKPYPG 850
851 AELSSMGAIVWAVRAKDYNKAMEFDCLLGISSEFIVLIEQETKSVAFNCS 900
901 CRDVIGWTSSDTSLKIFYERGECVSVESFISGEDIKEIVRRLQFVSKGCE 950
951 SVEMTLRRNGLGQLGFHVNYEGIVADVEPYGYAWQAGLRQGSRLVEICKV 1000
1001 AVATLSHEQMIDLLRTSVTVKVVIIPPHDDCTPRRSCSETYRMPVMEYQM 1050
1051 NEGISYEFKFPFRNNNKWQRNASKGAHSPQVPSQLQSPMTSRLNAGKGDG 1100
1101 KMPPPERAANIPRSISSDGRPLERRLSPGSDIYVTVSSMALARSQCRNSP 1150
1151 SNLSSSSETGSGGGTYRQKSMPEGFGVSRRSPASIDRQNTQSDISGSGKS 1200
1201 TPSWQRSEDSLADQMEPTCHLPAVSKVLPAFRESPSGRLMRQDPVVHLSP 1250
1251 NKQGHSDSHYSSHSSSNTLSSNASSAHSDEKWYDGDRTESDLNSYNYLQG 1300
1301 TSADSGIDTASYGPSHGSTASLGASTSSPRSGPGKEKVAPLWHSSSEVLS 1350
1351 LADRTLETEGHGMDRKAESSLSLDIHSKSQGGSSPLSRENSTFSINDAAS 1400
1401 HTSTMSSRHSASPVVFSSARSSPKEELHPTASSQLAPSFSSSSSSSSGPR 1450
1451 TFYPRQGATSKYLIGWKKPEGTINSVGFMDTRKRHQSDGNEIAHTRLRAS 1500
1501 TRDLQASPKPTSKSTIEEDLKKLIDLESPTPESQKNFKFHALSSPQSPFP 1550
1551 TTPTSRRALHRTLSDESIYSSQREHFFTSRASLLDQALPNDVLFSSTYPS 1600
1601 LPKSLPLRRPSYTLGMKSLHGEFSASDSSLTDIQETRRQPIPDPGLMPLP 1650
1651 DAASDLDWSNLVDAAKAYEVQRASFFAASDENHRPLSAASNSDQLEEQAL 1700
1701 VQMKSYSSKDPSPTLASKVDQLEGMLKMLREDLKKEKEDKAQLQAEVEHL 1750
1751 REDNLRLQEESQNASDKLKKFTEWVFNTIDMS 1782
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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