 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P40851 from www.uniprot.org...
The NucPred score for your sequence is 0.76 (see score help below)
1 MSLREVTNYEVSFYIPLSYSNRTHKVCKLPNGILALIISDPTDTSSSCSL 50
51 TVCTGSHNDPKDIAGLAHLCEHMILSAGSKKYPDPGLFHTLIAKNNGSQN 100
101 AFTTGEQTTFYFELPNTQNNGEFTFESILDVFASFFKEPLFNPLLISKEI 150
151 YAIQSEHEGNISSTTKIFYHAARILANPDHPFSRFSTGNIHSLSSIPQLK 200
201 KIKLKSSLNTYFENNFFGENITLCIRGPQSVNILTKLALSKFGDIKPKSA 250
251 VKERSISIRTRSFRRSKSLKKRQDSSKNDYSDLKTFKILNTTWEKKYKNT 300
301 MCFQQFPECNSIFINSNKVPIMRLLFPVSDKNTRFTKDDIKIYSHLWCEL 350
351 FGDESPGSLSYYLASKGWLTGCFAFTSEFAIGDIGLILELELTNSGWENI 400
401 KRITTIVLNRLLPSFYVMNIDYLITFLKEQNLIDLVSFLYQSSEDLPMEE 450
451 CSKLSGILQDDLECLTPPNIFKGFKSLIEIDDPNIEKYENTKANIQWWTG 500
501 QAIKFQNFLKSFMNHDNMRLLLLGNIKSGNIFDKMKNKSDICTDFFYEFE 550
551 YYTANVHLASDNKFHSNSSYEFNFPTGNLFLPDCVSDPLKLQQLFLECSL 600
601 KSKFATLRPQIYSEPTRTKPQLVSENQNYEMWILKEDPNFASDNKSVVSF 650
651 EVLGLGIKPSPEATIHLEVLAQALFIITSSFLYPALRIGYTYEIASSSKG 700
701 NVTLRFTISGFPEGVFTIVKTFVDTLKLIATDPTFLSKDTLRKARILVRN 750
751 KYKNASSDNCVKLASVGLLIVLEKYIWTLEDRINALELTELESFEKFCFL 800
801 FWRNPKHLVLFMQGSLEYADAINRYLNNNFTQHLKISNEGSKPTIRLYPP 850
851 PSTKDLDQGTNAFISYNGHQDDPNNSIVYFIQTAQRDDIKNLTLTFLTEY 900
901 LFSLTLVPDLRNKKQIGYIVLGGLRVLTDTVGIHITVMSGSSGHNLETRI 950
951 NEYLSYLQLQVLNRFTEFDFRRILLEPFLNLLKQNSTKQFEGSAGPVDLL 1000
1001 NEIVANVQNGDNYTLNNKQMRQHRKVRNKIAEGRLNFQEDHEMIDISFLQ 1050
1051 KLTLKKYLAFFESKISIYSAQRSKLSIMITSPMAEKEIASRKMFLQLEAF 1100
1101 LKINGFAIKNEDLKKIVEHSKGNPILLVKNLFTYFRRRNEVFKLGTVVLQ 1150
1151 EILKIIGMNLKQRYGSILGFSSQDGEGQEIEKFWNNDTSPIVPLQELPEP 1200
1201 NFFRKAAF 1208
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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