 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O96935 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MKLTKGCAYKYIIFTVLILANILYDNKKRCMIKKNLRISSCGIISRLLKS 50
51 NSNYNSFNKNYNFTSAISELQFSNFWNLDILQKDIFSNIHNNKNKPQSYI 100
101 IHKRLMSEKGDNNNNNHQNNNGNDNKKRLGSVVNNEENTCSDKRMKPFEE 150
151 GHGITQVDKMNNNSDHLQQNGVMNLNSNNVENNNNNNSVVVKKNEPKIHY 200
201 RKDYKPSGFIINNVTLNINIHDNETIVRSVLDMDISKHNVGEDLVFDGVG 250
251 LKINEISINNKKLVEGEEYTYDNEFLTIFSKFVPKSKFAFSSEVIIHPET 300
301 NYALTGLYKSKNIIVSQCEATGFRRITFFIDRPDMMAKYDVTVTADKEKY 350
351 PVLLSNGDKVNEFEIPGGRHGARFNDPHLKPCYLFAVVAGDLKHLSATYI 400
401 TKYTKKKVELYVFSEEKYVSKLQWALECLKKSMAFDEDYFGLEYDLSRLN 450
451 LVAVSDFNVGAMENKGLNIFNANSLLASKKNSIDFSYARILTVVGHEYFH 500
501 NYTGNRVTLRDWFQLTLKEGLTVHRENLFSEEMTKTVTTRLSHVDLLRSV 550
551 QFLEDSSPLSHPIRPESYVSMENFYTTTVYDKGSEVMRMYLTILGEEYYK 600
601 KGFDIYIKKNDGNTATCEDFNYAMEQAYKMKKADNSANLNQYLLWFSQSG 650
651 TPHVSFKYNYDAEKKQYSIHVNQYTKPDENQKEKKPLFIPISVGLINPEN 700
701 GKEMISQTTLELTKESDTFVFNNIAVKPIPSLFRGFSAPVYIEDNLTDEE 750
751 RILLLKYDSDAFVRYNSCTNIYMKQILMNYNEFLKAKNEKLESFNLTPVN 800
801 AQFIDAIKYLLEDPHADAGFKSYIVSLPQDRYIINFVSNLDTDVLADTKE 850
851 YIYKQIGDKLNDVYYKMFKSLEAKADDLTYFNDESHVDFDQMNMRTLRNT 900
901 LLSLLSKAQYPNILNEIIEHSKSPYPSNWLTSLSVSAYFDKYFELYDKTY 950
951 KLSKDDELLLQEWLKTVSRSDRKDIYEILKKLENEVLKDSKNPNDIRAVY 1000
1001 LPFTNNLRRFHDISGKGYKLIAEVITKTDKFNPMVATQLCEPFKLWNKLD 1050
1051 TKRQELMLNEMNTMLQEPNISNNLKEYLLRLTNKL 1085
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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