 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P38427 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MALIVASLFLPYQPQFELDTSLPENSQVDSSLVNIQAMANDQQQQRALSN 50
51 NISQESLVAPAPEQGVPPAISRSATRSPSAFNRASSTTNTATLDDLVSSD 100
101 IFMENLTANATTSHTPTSKTMLKPRKNGSVERFFSPSSNIPTDRIASPIQ 150
151 HEHDSGSRIASPIQQQQQDPTTNLLKNVNKSLLVHSLLNNTSQTSLEGPN 200
201 NHIVTPKSRAGNRPTSAATSLVNRTKQGSASSGSSGSSAPPSIKRITPHL 250
251 TASAAKQRPLLAKQPSNLKYSELADISSSETSSQHNESDPDDLTTAPDEE 300
301 YVSDLEMDDAKQDYKVPKFGGYSNKSKLKKYALLRSSQELFSRLPWSIVP 350
351 SIKGNGAMKNAINTAVLENIIPHRHVKWVGTVGIPTDEIPENILANISDS 400
401 LKDKYDSYPVLTDDDTFKAAYKNYCKQILWPTLHYQIPDNPNSKAFEDHS 450
451 WKFYRNLNQRFADAIVKIYKKGDTIWIHDYHLMLVPQMVRDVLPFAKIGF 500
501 TLHVSFPSSEVFRCLAQREKILEGLTGADFVGFQTREYARHFLQTSNRLL 550
551 MADVVHDEELKYNGRVVSVRFTPVGIDAFDLQSQLKDGSVMQWRQLIRER 600
601 WQGKKLIVCRDQFDRIRGIHKKLLAYEKFLVENPEYVEKSTLIQICIGSS 650
651 KDVELERQIMIVVDRINSLSTNISISQPVVFLHQDLDFSQYLALSSEADL 700
701 FVVSSLREGMNLTCHEFIVCSEDKNAPLLLSEFTGSASLLNDGAIIINPW 750
751 DTKNFSQAILKGLEMPFDKRRPQWKKLMKDIINNDSTNWIKTSLQDIHIS 800
801 WQFNQEGSKIFKLNTKTLMEDYQSSKKRMFVFNIAEPPSSRMISILNDMT 850
851 SKGNIVYIMNSFPKPILENLYSRVQNIGLIAENGAYVSLNGVWYNIVDQV 900
901 DWRNDVAKILEDKVERLPGSYYKINESMIKFHTENAEDQDRVASVIGDAI 950
951 THINTVFDHRGIHAYVYKNVVSVQQVGLSLSAAQFLFRFYNSASDPLDTS 1000
1001 SGQITNIQTPSQQNPSDQEQQPPASPTVSMNHIDFACVSGSSSPVLEPLF 1050
1051 KLVNDEASEGQVKAGHAIVYGDATSTYAKEHVNGLNELFTIISRIIED 1098
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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