 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q27995 from www.uniprot.org...
The NucPred score for your sequence is 0.60 (see score help below)
1 MACPWQFLFKIKSQKVDLATELDINNNVGKFYQPPSSPVTQDDPKRHSPG 50
51 KHGNESPQPLTGTVKTSPESLSKLDAPPSACPRHVRIKNWGSGVTFQDTL 100
101 HQKAKGDLSCKSKSCLASIMNPKSLTIGPRDKPTPPDELLPQAIEFVNQY 150
151 YGSFKEAKIEEHLARVEAVTKEIETTGTYQLTGDELIFATKQAWRNAPRC 200
201 IGRIQWSNLQVFDARSCSTAQEMFEHICRHVRYATNNGNIRSAITVFPQR 250
251 SDGKHDFRVWNAQLIRYAGYQMPDGSIRGDPANVEFTQLCIDLGWKPKYG 300
301 RFDVLPLVLQADGRDPELFEIPPDLVLEVPMEHPRYEWFRELELKWYALP 350
351 AVANMLLEVGGLEFPGCPFNGWYMGTEVGVRDFCDAQRYNILEEVGRRMG 400
401 LETHKVASLWKDRAVVEINVAVLHSFQKQNVTIMDHHSAAESFMKYMQNE 450
451 YRSRGGCPADWIWLVPPISGSITPVFHQEMLNYVLSPFYYYQVEPWKTHV 500
501 WQDERRRPQRREIRFKVLVKAVFFASVLMHKAMASRVRATILFATETGRS 550
551 ETLAQDLGALFSCAFNPKVLCMDQYQLSHLEEEQLLLVVTSTFGNGDSPG 600
601 NGEKLKKSLLMLKELTNTFRYAVFGLGSSMYPQFCAFAHDIDQKLSQLGA 650
651 SQLAPTGEGDELSGQEEAFRSWAVQTFKAACETFDVSGKHHIEIPKLYTS 700
701 NVTWDPQHYRLVQDSEPLDLNKALSSMHAKHVFTMRLKSQQNLQSPKSSR 750
751 TTLLVELSCEGSQAPSYLPGEHLGVFPCNQPALVQGILERVVDGPAPHQP 800
801 VRLETLCENGSYWVKDKRLPPCSLSQALTYFLDITTPPTQLLLRKLAQLA 850
851 TEEAEKQRLETLCQPSDYNKWKFTNSPTFLEVLEEFPSLRVSASFLLSQL 900
901 PILKPRYYSISSSRDLTPTEIHLTVAVLTYRTRDGQGPLHHGVCSTWLSS 950
951 LKPQDPVPCFVRSASGFQLPEDRSRPCILIGPGTGIAPFRSFWQQRLHEA 1000
1001 EHKGLQGGRMTLVFGCRRPEEDHLYWEEMLEMARKGVLHEVHTAYSRLPD 1050
1051 QPKVYVQDILRQRLAGEVLRVLHEEQGHLYVCGDVRMARDVARTLKQLMA 1100
1101 TALSLNEEQVEDYFFQLKNQKRYHEDIFGAVFPYEVKKDGAAGLPSNPRA 1150
1151 PGAHRS 1156
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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