 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8VDJ3 from www.uniprot.org...
The NucPred score for your sequence is 0.68 (see score help below)
1 MSSVAVLTQESFAEHRSGLVPQQIKVATLNSEEENDPPTYKDAFPPLPEK 50
51 AACLESAQEPAGAWSNKIRPIKASVITQVFHVPLEERKYKDMNQFGEGEQ 100
101 AKICLEIMQRTGAHLELSLAKDQGLSIMVSGKLDAVMKARKDIVARLQTQ 150
151 ASATVPIPKEHHRFVIGKNGEKLQDLELKTATKIQIPRPDDPSNQIKITG 200
201 TKEGIEKARHEVLLISAEQDKRAVERLEVEKAFHPFIAGPYNRLVGEIMQ 250
251 ETGTRINIPPPSVNRTEIVFTGEKEQLAQAVARIKKIYEEKKKKTTTIAV 300
301 EVKKSQHKYVIGPKGNSLQEILERTGVSVEIPPSDSISETVILRGEPEKL 350
351 GQALTEVYAKANSFTVSSVSAPSWLHRFIIGKKGQNLAKITQQMPKVHIE 400
401 FTEGEDKITLEGPTEDVNVAQEQIEGMVKDLINRMDYVEINIDHKFHRHL 450
451 IGKSGANINRIKDQYKVSVRIPPDSEKSNLIRIEGDPQGVQQAKRELLEL 500
501 ASRMENERTKDLIIEQRFHRTIIGQKGERIREIRDKFPEVIINFPDPAQK 550
551 SDIVQLRGPKNEVEKCTKYMQKMVADLVENSYSISVPIFKQFHKNIIGKG 600
601 GANIKKIREESNTKIDLPAENSNSETIIITGKRANCEAARSRILSIQKDL 650
651 ANIAEVEVSIPAKLHNSLIGTKGRLIRSIMEECGGVHIHFPVEGSGSDTV 700
701 VIRGPSSDVEKAKKQLLHLAEEKQTKSFTVDIRAKPEYHKFLIGKGGGKI 750
751 RKVRDSTGARIIFPAAEDKDQDLITIIGKEDAVREAQKELEALIQNLENV 800
801 VEDYMLVDPKHHRHFVIRRGQVLREIAEEYGGVMVSFPRSGTQSDKVTLK 850
851 GAKDCVEAAKKRIQEIIEDLEAQVTVECAIPQKFHRSVMGPKGSRIQQIT 900
901 RDYNVQIKFPDREENPVHSVEPSIQENGDEAGEGREAKETDPGSPRRCDI 950
951 IIISGRKEKCEAAKEALEALVPVTIEVEVPFDLHRYIIGQKGSGIRKMMD 1000
1001 EFEVNIHVPAPELQSDTIAITGLAANLDRAKAGLLDRVKELQAEQEDRAL 1050
1051 RSFKLSVTVDPKYHPKIIGRKGAVITQIRLEHEVNIQFPDKDDGNQPQDQ 1100
1101 ITITGYEKNTEAARDAILKIVGELEQMVSEDVPLDHRVHARIIGARGKAI 1150
1151 RKIMDEFKVDIRFPQSGAPDPNCVTVTGLPENVEEAIDHILNLEEEYLAD 1200
1201 VVDSEALQVYMKPPAHEESRAPSKGFVVRDAPWTSNSSEKAPDMSSSEEF 1250
1251 PSFGAQVAPKTLPWGPKR 1268
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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