 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q40392 from www.uniprot.org...
The NucPred score for your sequence is 0.77 (see score help below)
1 MASSSSSSRWSYDVFLSFRGEDTRKTFTSHLYEVLNDKGIKTFQDDKRLE 50
51 YGATIPGELCKAIEESQFAIVVFSENYATSRWCLNELVKIMECKTRFKQT 100
101 VIPIFYDVDPSHVRNQKESFAKAFEEHETKYKDDVEGIQRWRIALNEAAN 150
151 LKGSCDNRDKTDADCIRQIVDQISSKLCKISLSYLQNIVGIDTHLEKIES 200
201 LLEIGINGVRIMGIWGMGGVGKTTIARAIFDTLLGRMDSSYQFDGACFLK 250
251 DIKENKRGMHSLQNALLSELLREKANYNNEEDGKHQMASRLRSKKVLIVL 300
301 DDIDNKDHYLEYLAGDLDWFGNGSRIIITTRDKHLIEKNDIIYEVTALPD 350
351 HESIQLFKQHAFGKEVPNENFEKLSLEVVNYAKGLPLALKVWGSLLHNLR 400
401 LTEWKSAIEHMKNNSYSGIIDKLKISYDGLEPKQQEMFLDIACFLRGEEK 450
451 DYILQILESCHIGAEYGLRILIDKSLVFISEYNQVQMHDLIQDMGKYIVN 500
501 FQKDPGERSRLWLAKEVEEVMSNNTGTMAMEAIWVSSYSSTLRFSNQAVK 550
551 NMKRLRVFNMGRSSTHYAIDYLPNNLRCFVCTNYPWESFPSTFELKMLVH 600
601 LQLRHNSLRHLWTETKHLPSLRRIDLSWSKRLTRTPDFTGMPNLEYVNLY 650
651 QCSNLEEVHHSLGCCSKVIGLYLNDCKSLKRFPCVNVESLEYLGLRSCDS 700
701 LEKLPEIYGRMKPEIQIHMQGSGIRELPSSIFQYKTHVTKLLLWNMKNLV 750
751 ALPSSICRLKSLVSLSVSGCSKLESLPEEIGDLDNLRVFDASDTLILRPP 800
801 SSIIRLNKLIILMFRGFKDGVHFEFPPVAEGLHSLEYLNLSYCNLIDGGL 850
851 PEEIGSLSSLKKLDLSRNNFEHLPSSIAQLGALQSLDLKDCQRLTQLPEL 900
901 PPELNELHVDCHMALKFIHYLVTKRKKLHRVKLDDAHNDTMYNLFAYTMF 950
951 QNISSMRHDISASDSLSLTVFTGQPYPEKIPSWFHHQGWDSSVSVNLPEN 1000
1001 WYIPDKFLGFAVCYSRSLIDTTAHLIPVCDDKMSRMTQKLALSECDTESS 1050
1051 NYSEWDIHFFFVPFAGLWDTSKANGKTPNDYGIIRLSFSGEEKMYGLRLL 1100
1101 YKEGPEVNALLQMRENSNEPTEHSTGIRRTQYNNRTSFYELING 1144
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.) |
Go back to the NucPred Home Page.