 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6PNC0 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MNLHQVLTGAVNPGDHCFAVGSVGEQRFTAYASGCDIVILGSNFERLQII 50
51 PGAKHGNIQVGCVDCSMQQGKIAASYGNVISVFEPVSLPKKRKNLEFYSQ 100
101 WQKSGQFFLDSIAHNITWDPAGNRLLTGSSCLQLWCNSRKQTEDENPDKT 150
151 DLNFGNWMCIWHCKTASQVHLMKFSPDGEFFATAGKDDCLLKVWYNVENW 200
201 RPAVTSPDKNSEKQSQGEIDFSFVYLAHPRAVNGFSWRKTSKYMPRASVC 250
251 NVLLTCCKDNVCRLWVETFLPNDCFLYGSDCNHWCEPVSLTNNLKRNASS 300
301 KDRVQSALEVNLRPFRRGRSRSLALVAHTGYLPHQQDPHHAHRNTPLHAN 350
351 ALCHFHIAASINPATDIPLLPSITSLSLNENEEKCGPFVVHWLNNKELHF 400
401 TLSMEVFLQQLRKSFEQPSSEASVEDSIQADLKSDEELDDGVDDLKINHE 450
451 KKELDEDKMLPSSSFTPLSSAAVDHQIEVLLSEWSKNADMLFSIHPMDGS 500
501 LLVWHVDWLDEYQPGMFRQVQVSFVSRIPVAFPTGDANSLCKSIVMYACT 550
551 KNVDLAIQQGKQRPTGLTRSTSMLISSAHSKSSNNLKLSIFTPNVMMISK 600
601 HADGSLNQWLVSFAEESAFSTVLSISHKSRYCGHRFHLNDLACHSVLPLL 650
651 LTTSHHNALRTPNVGNQKQAHDAVNTEECSLAQQNKSNVDMAFQDPNAIY 700
701 SELILWRVDPVGPLSFSGGVSELARINSLHVSAFSNVAWLPTLIPSYCLG 750
751 AYCNSPSACFVASDGQYLRLYEAVIDAKKLLYELSNPEISKYVGEVFNIV 800
801 SQQSTARPGCIIALDSITKLHGRKTQLLHVFQEDFILNNLEKKRLGVDNI 850
851 LLDSDSSCNGFSEKFYLVVIECTEDNRSLLRMWDLHLRSTPVSLDERIDT 900
901 KISEASWLPEEHYSSSPEKILSPFSQKFQACRANLQSTSKLSLFSEMVYS 950
951 KELDLPEGVEIISVKPSAGHLSSSSIYPVCSAPYLLATSCSDDKVRFWRC 1000
1001 RVTNGESATSKNGKLDVVYVWEEWPLLIEDGLENNSSVTVPGRPVEVSCA 1050
1051 HTSRLAVAYKQPTGNSRSQEFVMHVSIFECESTGGSCWILEQTIHLDELS 1100
1101 TVLDSGISIDSNLVAYNKQETYLVSKESITSNTKHLVHLDWMSREDGSHI 1150
1151 LTVGIGSKLFMYGPMAGKVQDQTGKENQAFPLWDSTKIVPLSKFVLLRSV 1200
1201 DLVSSVEGAPPFPVSLSWVRDGILVVGMDCEMHVYSQWQPSNKQEPVISE 1250
1251 SYNGSTPSILSLIKQSNSSSSGLHPPKKTLTRSMTSLAQKICGKKSIFDP 1300
1301 SVDMEDSGLFEAAHVLSPTLPQYHPLQLLELMDLGKVRRAKAILSHLVKC 1350
1351 IAGEVVALNEAESNHERRLRSLTISASGSTTRDPQAFNKADSRDYTEIDS 1400
1401 VPPLPLYALLAADDDSYCSSLEKTGSESSLKKSKQLSKESYDELFQTSVL 1450
1451 MSDNHMLETDEENTQPRVIDLSQYSPTYFGPEHAQVLSGHLLHSSLPGLT 1500
1501 RMEQMSLMALADTIATTSTDIGESRDRNQGGETLDECGLKFLLAVRLHTF 1550
1551 LTTSLPAYRAQLLHQGLSTGHFAWAFHSVAEEELLNMLPAMQKDDPTWSE 1600
1601 LRAMGVGWWVRNARILRRCIEKVAKAAFHRNNDPLDAAIFYLAMKKKAVI 1650
1651 WGLYRSQKDTKMTQFFGHNFEEERWRKAALKNAFSLLGKQRFEHSAAFFL 1700
1701 LGGCLKDAIEVCLEKLNDIQLALVIARLFESEFDKSATYKSILRKKVLGI 1750
1751 GSPASELSSSSINAHHDPFLRSMAHWILEDYSAALETLIKQPVTEDEDQV 1800
1801 MMSACNPIVFNFYNYLRTHPLLLRRHFGSSSETFSTHMTLAGKSGLAGTI 1850
1851 NLSERRLFFTTASAHLKAGCPMLALEVLSKMPKVSKKAKPCCRGSSFLTS 1900
1901 KDSSLKLDVREDKCCAADWSPSLTNGLESSSEGSSERHSHSTLSFDWSQP 1950
1951 SVVFQDDSLELKWDSDNDEENEDPPISMKEIRPLQRKTVKEIDELSSYTD 2000
2001 SLSTLDENDILNPSEDIIAVQLKFRACLKILTVELRTLSTGYEIDGGKLR 2050
2051 YQLYHWLEKEVVALQRTCDFCSDADQLQTTFSQSADESGSTEDADDLHHQ 2100
2101 TKVKQLRESFQEKRQWLLKYQSLLRMFLSYCVLHGSHGGGLASVRMELIL 2150
2151 LLQESQQETAEPIFSNPLSEQTSVPLLFACTASAKTVVANPLLHLSNLTH 2200
2201 DILHAIINFDSPPHPDSQTNKVYVMHTLAASLSACIYQCLCGSHNYSSFQ 2250
2251 TNQFTGMVYQTVLLAHRHSLRTGSLDESVTPNTSPAQWPGINFLIQLLNS 2300
2301 SGEEAQSGLTVLLCEILTAVYLSLFIHGLATHSSNELFRIVAHPLNEKMW 2350
2351 SAVFGGGAHVPSKGQANSKALSVEGEKQNRHISPSKVSARESPVSSSSGN 2400
2401 QEPPAVKEKFVPPELSIWDYFIAKPFLPPSQSRAEYDSEESLESDDEEEE 2450
2451 DDDDALPSGLQLHEHSNSNSFSWSLMRLAMVQLVLNNLKTFYPFAGHDLA 2500
2501 ELPVSSPLCHAVLKTLQCWEQVLLRRLEIHGGPPQNYISSHTSEENVSAG 2550
2551 PAILRHKALLEPTNTPFKSKNHLALSVKRLWQYLVKQEEIQETFIRNIFT 2600
2601 KKRCLNEIEADLGYPGGKARIIHKESDIITAFAVNRANRNCIAIASSHDV 2650
2651 QELDVSAILATQIYTWVDDDTETETKGSEDFLVIHARDDLSAVQGSTPYT 2700
2701 HSNPGTPINMPWLGSTQTGRGASVMLKKAINNVRRMTSHPTLPYYLTGAQ 2750
2751 DGSVRMFEWGHSQQITCFRSGGNSRITRMRFNYQGNKFGIVDADGYLSLY 2800
2801 QTNWKCCPVTGSMPKPYLAWQCHNKTANDFVFVSSSSLIATAGLSSDNRN 2850
2851 ICLWDTLVAPANSLVHAFTCHDSGATVLAYAPKHQLLISGGRKGFTCIFD 2900
2901 LRQRQQRQLFQSHDSPVKAIAIDPTEEYFVTGSAEGNIKIWSLSSFSLLH 2950
2951 TFINEHARQSIFRNIGTGVMQIETGPANHIFSCGADGTMKMRILPDQFSP 3000
3001 LNEVLKNDVKFML 3013
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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