 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q04439 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MAILKRGARKKVHQEPAKRSANIKKATFDSSKKKEVGVSDLTLLSKISDE 50
51 AINENLKKRFLNATIYTYIGHVLISVNPFRDLGIYTDAVMNEYKGKNRLE 100
101 VPPHVFAIAESMYYNMKSYNENQCVIISGESGAGKTEAAKRIMQYIAAAS 150
151 STHTESIGKIKDMVLATNPLLESFGCAKTLRNNNSSRHGKYLEIKFNNQF 200
201 EPCAGNITNYLLEKQRVVSQIKNERNFHIFYQFTKGASDAYRQTFGVQKP 250
251 EQYVYTAAAGCISAETIDDLQDYQETLKAMRVIGLGQEEQDQIFRMLAAI 300
301 LWIGNVSFIENEEGNAQVRDTSVTDFVAYLLQIDSQLLIKSLVERIMETN 350
351 HGMKRGSVYHVPLNIVQADAVRDALAKAIYNNLFDWIVSRVNKSLQAFPG 400
401 AEKSIGILDIYGFEIFEHNSFEQICINYVNEKLQQIFIQLTLKSEQETYE 450
451 REKIQWTPIKYFDNKVVCDLIEARRPPGIFAAMNDSVATAHADSNAADQA 500
501 FAQRLNLFTTNPHFDLRSNKFVIKHYAGDVTYDIDGITDKNKDQLQKDLV 550
551 ELIGTTTNTFLATIFPDTVDRESKRRPPTAGDKIIKSANDLVETLSKAQP 600
601 SYIRTIKPNETKSPNDYDDRQVLHQIKYLGLQENVRIRRAGFAYRQVFEK 650
651 FVERFYLLSPHCSYAGDYTWQGDTLDAVKYILQDSSIPQQEYQLGVTSVF 700
701 IKTPETLFALEHMRDRYWHNMAARIQRAWRRFLQRRIDAATKIQRTIRER 750
751 KEGNKYEKLRDYGTKVLGGRKERRSMSLLGYRAFMGDYLSCNESKSKGAY 800
801 IKRQVSIKEKVIFSIHGEALHTKFGRSAQRLKKTFLLTPTTLYIVGQTLV 850
851 QNAMTYTQDYKIDVRNIQAVSLTNLQDDWVAIKLASSGQPDPLINTYFKT 900
901 ELITHLKRLNDKIQIKIGSAIEYQKKPGKLHSVKCQINESAPKYGDIYKS 950
951 STISVRRGNPPNSQVHKKPRKKSSISSGYHASSSQATRRPVSIAAAQHVP 1000
1001 TAPASRHSKKPAPPPPGMQNKAATRRSVPNPASTLTASQSNARPSPPTAA 1050
1051 TRATPAATPAAAAMGSGRQANIPPPPPPPPPSSKPKEPMFEAAYDFPGSG 1100
1101 SPSELPLKKGDVIYITREEPSGWSLGKLLDGSKEGWVPTAYMKPHSGNNN 1150
1151 IPTPPQNRDVPKPVLNSVQHDNTSANVIPAAAQASLGDGLANALAARANK 1200
1201 MRLESDDEEANEDEEEDDW 1219
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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