 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O13353 from www.uniprot.org...
The NucPred score for your sequence is 0.80 (see score help below)
1 MSLPERPGAKASYEQRNSYRKSPSRRNRPNDIEASGYYPVTGGQHQRGPS 50
51 VNSFAETIRSPNSNIESAPLSPSAEQIEHGSDQPFQRKRSLIRPERNRID 100
101 RDHPNYHYRKHAAKMNTLPSSTGNDPVLEDVSGATESGPPSGSNSASGSG 150
151 VREENIPRKSRKASGRETVAEKSDNTRRRVSTRNSKIVKEGKRKEKIPEQ 200
201 LRPPSAWNVYCAVITFWSPDFIMKCCGMPAKAQRRAWREKIGLISLILII 250
251 MGVVGFLTFGFNQAVCGGPVLRLHINSVDRSYMIFHGTAYNLDGSHHPVA 300
301 EGIPKRLDGTGANVVYDLPEGYGGTDGSFMFQNVNGKCKGLITKAPNSDV 350
351 PSEGDNLAWYFPCHARNQDGSSQPNMTYPYYFGYACHTTPLARSTFYTQL 400
401 DKSADVYFTWADIRNNSRNLFVYSGNVLDLDLLFWFNRDQVNIPRRFEEL 450
451 RDKNNAANRAIRGRDATRTFMASGDRQIAECFEDIIKVGTVDTDTVGCIA 500
501 AKVVLYVSLALILSVVGARFTLALIFQWFISKNYAADKTSQTSDKRKRNK 550
551 QIEDWSEDIYRAPPRMPGDVGSSVAGASSSDHTSKRSSFLPTTSRFSTVY 600
601 GAERSARNKSMPTTMASQASGGYMGPSSTAYRETNESRTSFLKSDPYATN 650
651 TAPIEGPGPSGFIHDSVVPQPPSDWMPFGFPLAHTICLVTAYSEGELGLR 700
701 TTLDSVAMTDYPNSHKVILVICDGIIKGKGESKSTPEYVLDMMKDHTIPV 750
751 EDVEAFSYVAVASGSKRHNMAKIYAGFYDYGTQSNIPLDKQQRVPMMVVV 800
801 KCGTPDEMVKSKPGNRGKRDSQIILMSFLQKVMFDERMTELEYEMFNGLW 850
851 KVTGISPDFYEIVLMVDADTKVFPDSLTHMISAMVKDPEIMGLCGETKIA 900
901 NKRDSWVSAIQVFEYFISHHLAKSFESVFGGVTCLPGCFCMYRIKAPKGA 950
951 QNYWVPILANPDVVEHYSENVVDTLHKKNLLLLGEDRYLTTLMLRTFPKR 1000
1001 KQVFVPQAVCKTTVPDSFMVLLSQRRRWINSTIHNLMELVLVRDLCGTFC 1050
1051 FSMQFVIFIELIGTLVLPAAIAFTFYVVIISIINQPPQIIPLVLLGLILG 1100
1101 LPAILIIITAHSWSYVLWMLIYLLSLPVWNFVLPAYAFWKFDDFSWGDTR 1150
1151 KTAGEKTKKAGIEYEGEFDSSKITMKRWAEFERDRRARQSQYWGSRENVT 1200
1201 GGVRTASGVWASAPPHHHQQQYDEYYSDA 1229
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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