 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8K389 from www.uniprot.org...
The NucPred score for your sequence is 0.75 (see score help below)
1 MDSGMEEEGALPGTLSGCSGLHPVLPSDLDVISDTSGLGNGVLPSMSEEK 50
51 VSPTRARNMKDFENQITELKKENFNLKLRIYFLEERIQQEFAGPTEHIYK 100
101 TNIELKVEVESLKRELQEKDQLLVKASKAVESLAERGGSEVQRVKEDARK 150
151 KVQQVEDLLTKRIHLLEEDVKAAQAELEKAFAGTETEKALRLSLESKLSA 200
201 MKKMQEGDLEMTLALEEKDRLIEELKLSLKSKEALIQCLKEEKSQMASPD 250
251 ENVSSGELRGLSATLREEKERDAEEWQKERNHFEERIQALQEDLREKERE 300
301 IATEKKNNLKSYKAIQGLTMALKSKEREVEELDSKIKEVTTDSTKGREDP 350
351 LKTQIPRFQLREGSEDCEAALVEKEALLAKLHSENVTKSTENHRLLRNVK 400
401 KVTQELNDLKKEKLRLEQALEEAHQEGNRGARTIHDLRNEVEKLRKEVSE 450
451 REKAVEKHYKSLPGESKTKFHTQEQVVRSLTGSGSQEDLLLQKSNEKDLE 500
501 AIQQNCYLMTAEELKFGSDGLITEKCSQQSPDSKLIFSKEKQQSEYEGLT 550
551 GDLKAEQNIYAHLAKTQDTDSVSNLQAELKEVLALRKQLEQDVLAYRNLQ 600
601 KALQEQLSEIRSREEEPFSFYSDQTSYLSICLEEHNQFQLEHFSQEELKK 650
651 KVSDLIQLVKDLHTDNQHLKKTIFDLSSVGFQGSDRLELTKQEELVASKE 700
701 DEDTLKFEADVETPFQSDQHLEQSREIMEDYAEGGCKSGYGRHMDSNILG 750
751 HDGAQTPGASEEHTLEDELLGLLATLFSKKATPLLESRPDLLKALGALLL 800
801 ERICLAEQGRPGDHLDSKTEKALQQVAVQLRDELGHSFPANSFSKSYNEV 850
851 KSMWGNWLVKTGDEDTVELKSVSVQTMAIEDTPHGFKPQSKRDAWAEKQE 900
901 EAIFSTELESEALGEMPGQQATHLSFPSAINPDAEKTGLLIQLKTPELLE 950
951 NLYNLPASPEVVVAQLQGQVLELQRELKEFKTRNKQLHEKLILAEAMMEG 1000
1001 LPVPNSALVNVPAAQAVVRTAFQDNPGEQEGPETTQSAGRDKDMDSDQYT 1050
1051 SFEIDSEICPPDDLALLPACKENLEDLLGPSSIATYLDSKSQLSVKVSVN 1100
1101 GTDQSENINIPDDTEDLKQKIHDLQTELEGYRNIIVQLLKHSQCSEAIIT 1150
1151 VLCGTEGAQDGLNKPKGHIDEEEMTFSSLHQVRYVKHMKILRPLTPEMID 1200
1201 GKMLESLKQQLVDQEQELQKEQDLNLELFGEIHDLQNKFQDLSPSRYDSL 1250
1251 VQSQARELSLQRQQIKDSHGICVIYRQHMSTMIKAFEELLQASDVDSCVA 1300
1301 EGFREQLTQCAGLLEQLERLFLHGKSARVEPHPQNELLKGLRTVEGNLPY 1350
1351 HHLLPESPEPSASHALSDDEMSEKSFLSRDPKPDSDTEKYPAMASHFPQD 1400
1401 LLMEHIQEIRTLRKHLEESIKTNEKLRKQLERQGSETDQGSRNVSACGLA 1450
1451 LHSSLTSEIHFLRKQNEALSMMLEKGSKDKQKESEKLRESLARKAESLEQ 1500
1501 LQLEYTSVREENERLQRDIIEKERHNQELTEEVCSSRQELSRVQEEAKSR 1550
1551 QQLLSQKDKLLQSLQMELKVYEKLAEEHPRLQQDGSKCPEASDNSFDLFE 1600
1601 STQAMAPKSASETPLLSGTDVDSLSCDSTSSATSPTSMPCLVAGHHMWAS 1650
1651 KSGHHMLGLIEDYDALYKQISWGQTLLAKMDVQTQEALSPTSHKLGPKGS 1700
1701 SSVPLSKFLSSMNTAKLVLEKASRLLKLFWRVSVPTNGQCSLHCEQIGEM 1750
1751 KAENTKLHKKLFEQEKKLQNTAKLLQQSKHQEKVIFDQLVITHQVLRKAR 1800
1801 GNLELRPGATRPGASSPSRPGS 1822
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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