 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q05808 from www.uniprot.org...
The NucPred score for your sequence is 0.65 (see score help below)
1 MWSTVALCLLVGLSYVSSSSPAWKDNTEYVYSVNGRTLTGLEETADQYSG 50
51 VFLEAKLHLSIRPDGKLQGRISEPKFAQILSQLPDGWKSEIPDSQISYKQ 100
101 LQLSQKPFQLVLENGLIKRLIVEKDTLNWEANIIKSIVSQFQMDLQGENA 150
151 LQNPTSSFPTNEYMDAVFKTMEETVTGKTETIYDIHRLPEYLVQSQPWIA 200
201 PQYKLKGEGDLIEVIKSKNYTNARDRPSYHYGFGEIEESEPTANKMGQFF 250
251 IRQSNSRAILTGKPSRYIIQSTYTVNKIMVNPILKNKEMGSITSMVNVTL 300
301 LEINNQQQQPEELSNPLDIGNLVYTYGQPKNNQVHSKLNENLMEDSSSEE 350
351 SSEQEMTHRRFRRSANSLTKQWRESSEEWNQQQQQPRPQLTRAPHSPLLP 400
401 SMVGYHGKSIKENKDFDIRQNVENLVTEISDEIKQSEKTISKHTLDKYTI 450
451 LNTLVRLMDEDDIQFVAEQMYSQMKNGQQRYTWSIFRDSVAEAGTGPALL 500
501 NIKKWIETKKIQKTEAAQVIGTLAQSTRFPTEEYMRKFFELATETQVRQQ 550
551 ETLNQTCILSYTNLVHKVYINRNESHNQFPVHAFGSFYTKKGREFVKTTV 600
601 IPHLKQELEKAISNADNNKIHVMIRALGNIGHKSILNVFQPYFEGEKQVS 650
651 QFQRLMMVACMDRLADCYPHIARSVFYKIYQNTAELPEIRVVAVHQLIRA 700
701 NPPVEMLQRMAQYTNTDSQEEVNAAVKSVIESSCKLESSKHAELRKAAQS 750
751 ARPLLTKKQYGMEQSYINLRDYVAEQMGLELHVQRTSHSSAESSFPKIMK 800
801 FQLHQHNHGMKQHILSTGGMISSIRELLNVLYRQTEVFQQEKSQRSQEQG 850
851 KDNEWSSANIARLMNYERDEREQLEAIIYAQVEDVQKLWSFDNQTLEHLP 900
901 EVIRQQEEIYRQGKDFSYVKLKQLNEMALSFPTEMGLPFLYTYDVPVLMK 950
951 VEGKIRALANPAISRNNKLTKPEQISTEIKARVTCTGKTQSHLSFVTPFD 1000
1001 HQIYMAGYDKNMYVSIPVNARLEMDVKSKEAKIEFEVEQQQQDSRLVHIT 1050
1051 STPYTSRSDVMAISPVALRPNTYVIKSHRNNHRYFDFNFGKKETGLTFRG 1100
1101 WGHHPEQSIGFNDLVSMWQSRGVAGVWEQLWDKCSTEYSEATISFIPSQS 1150
1151 TTRKATFRINVDQKYQKQPETQSPEDLLTLNQLSSKLQKDEPKQRQQEIK 1200
1201 KHVGSGINSALLSCSDISLEFEGDKKYEHVVGFAVAKSNADPKSRVMFYY 1250
1251 KNKNENKQGALEIRSEIPNTNGLNLDDSLDTEPSTKYNMRLQYGNSENDA 1300
1301 FEISAQAQLSRSQERKQYLINQDPLYHVCKEQMQQKNFQLPACQNMTIKA 1350
1351 NFLDHIKYQVQYQKLNWKLVETLEGMFKGLRVLYYPMTEIKSISSVGQNV 1400
1401 VEGEVQFQPEDFRQVNVTVRNTDEETVFFNISLNNELLRTLLVPHPVFHA 1450
1451 KCRFAGLMQGQQNYRPTCVIDQTTAQTFSNKTYSVNLDKEPTVVMQYVPK 1500
1501 DARVNGQQSKSVEQLLRESIENYVVLVRQVAANQKEVIINLNHPRTQGKT 1550
1551 VKIEMKPSEDRQKSARNPAAKVTIDGQEMHFDDKQIADKCDGYVQVYALP 1600
1601 NGEVKLEVEDAFYLIYDGQRVKVTATGNKLRDSVYGLCGRFSQDKHEDFT 1650
1651 VPSNCVTRDTRKFVESYQVEKGQQWRNSPSEQCIKKVLPLYTNVISNQNG 1700
1701 SQMRTKLASGTVMKHRYIEENGEICFTIRPLPVCNTSVKQVVTKNVPVHC 1750
1751 IQGTKTAYYYKSLIDQGGNPDFSRKSETRTARMEVAAQCN 1790
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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