 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9Z0R4 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MAQFPTPFGGSLDVWAITVEERAKHDQQFLSLKPIAGFITGDQARNFFFQ 50
51 SGLPQPVLAQIWALADMNNDGRMDQVEFSIAMKLIKLKLQGYQLPSTLPP 100
101 VMKQQPVAISSAPAFGIGGIASMPPLTAVAPVPMGSIPVVGMSPPLVSSV 150
151 PPAAVPPLANGAPPVIQPLPAFAHPAATLPKSSSFSRSGPGSQLNTKLQK 200
201 AQSFDVASAPPAAEWAVPQSSRLKYRQLFNSHDKTMSGHLTGPQARTILM 250
251 QSSLPQAQLASIWNLSDIDQDGKLTAEEFILAMHLIDVAMSGQPLPPVLP 300
301 PEYIPPSFRRVRSGSGMSVISSSSVDQRLPEEPSSEDEQQPEKKLPVTFE 350
351 DKKRENFERGSVELEKRRQALLEQQRKEQERLAQLERAEQERKERERQEQ 400
401 ERKRQLELEKQLEKQRELERQREEERRKEIERREAAKRELERQRQLEWER 450
451 NRRQELLNQRNKEQEGTVVLKARRKTLEFELEALNDKKHQLEGKLQDIRC 500
501 RLATQRQEIESTNKSRELRIAEITHLQQQLQESQQMLGRLIPEKQILSDQ 550
551 LKQVQQNSLHRDSLLTLKRALEAKELARQQLREQLDEVERETRSKLQEID 600
601 VFNNQLKELREIHSKQQLQKQRSLEAARLKQKEQERKSLELEKQKEDAQR 650
651 RVQERDKQWLEHVQQEEQPRPRKPHEEDRLKREDSVRKKEAEERAKPEMQ 700
701 DKQSRLFHPHQEPAKLATQAPWSTTEKGPLTISAQESVKVVYYRALYPFE 750
751 SRSHDEITIQPGDIVMVDESQTGEPGWLGGELKGKTGWFPANYAEKIPEN 800
801 EVPTPAKPVTDLTSAPAPKLALRETPAPLPVTSSEPSTTPNNWADFSSTW 850
851 PSSSNEKPETDNWDTWAAQPSLTVPSAGQLRQRSAFTPATATGSSPSPVL 900
901 GQGEKVEGLQAQALYPWRAKKDNHLNFNKSDVITVLEQQDMWWFGEVQGQ 950
951 KGWFPKSYVKLISGPVRKSTSIDTGPTESPASLKRVASPAAKPAIPGEEF 1000
1001 IAMYTYESSEQGDLTFQQGDVIVVTKKDGDWWTGTVGDKSGVFPSNYVRL 1050
1051 KDSEGSGTAGKTGSLGKKPEIAQVIASYAATGPEQLTLAPGQLILIRKKN 1100
1101 PGGWWEGELQARGKKRQIGWFPANYVKLLSPGTSKITPTELPKTAVQPAV 1150
1151 CQVIGMYDYTAQNDDELAFSKGQIINVLNKEDPDWWKGEVSGQVGLFPSN 1200
1201 YVKLTTDMDPSQQWCSDLHLLDMLTPTERKRQGYIHELIVTEENYVNDLQ 1250
1251 LVTEIFQKPLTESELLTEKEVAMIFVNWKELIMCNIKLLKALRVRKKMSG 1300
1301 EKMPVKMIGDILSAQLPHMQPYIRFCSCQLNGAALIQQKTDEAPDFKEFV 1350
1351 KRLAMDPRCKGMPLSSFILKPMQRVTRYPLIIKNILENTPENHPDHSHLK 1400
1401 HALEKAEELCSQVNEGVREKENSDRLEWIQAHVQCEGLSEQLVFNSVTNC 1450
1451 LGPRKFLHSGKLYKAKSNKELYGFLFNDFLLLTQITKPLGSSGTDKVFSP 1500
1501 KSNLQYKMYKTPIFLNEVLVKLPTDPSGDEPIFHISHIDRVYTLRAESIN 1550
1551 ERTAWVQKIKAASELYIETEKKKREKAYLVRSQRATGIGRLMVNVVEGIE 1600
1601 LKPCRSHGKSNPYCEVTMGSQCHITKTIQDTLNPKWNSNCQFFIRDLEQE 1650
1651 VLCITVFERDQFSPDDFLGRTEIRVADIKKDQGSKGPVTKCLLLHEVPTG 1700
1701 EIVVRLDLQLFDEP 1714
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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