 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13595 from www.uniprot.org...
The NucPred score for your sequence is 0.21 (see score help below)
1 MLRTKDLIWTLFFLGTAVSLQVDIVPSQGEISVGESKFFLCQVAGDAKDK 50
51 DISWFSPNGEKLSPNQQRISVVWNDDDSSTLTIYNANIDDAGIYKCVVTA 100
101 EDGTQSEATVNVKIFQKLMFKNAPTPQEFKEGEDAVIVCDVVSSLPPTII 150
151 WKHKGRDVILKKDVRFIVLSNNYLQIRGIKKTDEGTYRCEGRILARGEIN 200
201 FKDIQVIVNVPPTVQARQSIVNATANLGQSVTLVCDADGFPEPTMSWTKD 250
251 GEPIENEEEDDEKHIFSDDSSELTIRNVDKNDEAEYVCIAENKAGEQDAS 300
301 IHLKVFAKPKITYVENQTAMELEEQVTLTCEASGDPIPSITWRTSTRNIS 350
351 SEEKTLDGHMVVRSHARVSSLTLKSIQYTDAGEYICTASNTIGQDSQSMY 400
401 LEFQYAPKLQGPVAVYTWEGNQVNITCEVFAYPSATISWFRDGQLLPSSN 450
451 YSNIKIYNTPSASYLEVTPDSENDFGNYNCTAVNRIGQESLEFILVQADT 500
501 PSSPSIDRVEPYSSTAQVQFDEPEATGGVPILKYKAEWKSLGEESWHFKW 550
551 YDAKEANMEGIVTIMGLKPETRYSVRLAALNGKGLGEISAATEFKTQPVR 600
601 EPSAPKLEGQMGEDGNSIKVNLIKQDDGGSPIRHYLVKYRALASEWKPEI 650
651 RLPSGSDHVMLKSLDWNAEYEVYVVAENQQGKSKAAHFVFRTSAQPTAIP 700
701 ANGSPTAGLSTGAIVGILIVIFVLLLVVMDITCYFLNKCGLLMCIAVNLC 750
751 GKAGPGAKGKDMEEGKAAFSKDESKEPIVEVRTEEERTPNHDGGKHTEPN 800
801 ETTPLTEPELPADTTATVEDMLPSVTTVTTNSDTITETFATAQNSPTSET 850
851 TTLTSSIAPPATTVPDSNSVPAGQATPSKGVTASSSSPASAPKVAPLVDL 900
901 SDTPTSAPSASNLSSTVLANQGAVLSPSTPASAGETSKAPPASKASPAPT 950
951 PTPAGAASPLAAVAAPATDAPQAKQEAPSTKGPDPEPTQPGTVKNPPEAA 1000
1001 TAPASPKSKAATTNPSQGEDLKMDEGNFKTPDIDLAKDVFAALGSPRPAT 1050
1051 GASGQASELAPSPADSAVPPAPAKTEKGPVETKSEPPESEAKPAPTEVKT 1100
1101 VPNDATQTKENESKA 1115
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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