 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q64700 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MASGGNQSPPPPPAAAASSEEEEEDGDAADRAQPAGSPSHQIQQRFEELC 50
51 SRLNMDEAARAEAWSSYRSMSESYTLEGNDLHWLACALYVACRKSVPTVS 100
101 KGTAEGNYVSLTRILRCSEQSLIEFFNKMKKWEDMANLPPHFRERTERLE 150
151 RNFTVSAVIFKKYEPIFQDIFKYPQEEQPRQQRGRKQRRQPCTTSEIFHF 200
201 CWVLFIYAKGNFPMISDDLVNSYHLLLCALDLVYGNALQCSNRKELVNPN 250
251 FKGLSEDCHPKDSKASSDPPCVIEKLCSLHDGLVLEAKGIKEHFWKPYIR 300
301 KLFEKKLLKGKEENLTGFLEPGNFGESFKAVNKAYEEYVLAAGNLDERVF 350
351 LGEDAEEEVGTLSRCLSAASGTESAERTQMRDILQQHLDKSKALRVCTPL 400
401 TGVRYVQENSPCVTPVSTAAHSLSRLHTMLSGLRNAPSEKLERILRSCSR 450
451 DPTQAIADRLKEMYEIYSQHFQPDENFSNCAKEIANKHFRFAEMLYYKVL 500
501 ESVIEQEQKRLGDMDLSGVLEHDAFHRSLLACCLEVVAFSHKPPGNFPFI 550
551 AEIFDVPHYHFYKVIEVFIRAEDGLCREVVKHLNQIEEQILDHLAWKTKS 600
601 PLWDRIRDNENRVPTCEEVMPPQNLERTDEIYIAGSPLTPRRVGEVRADA 650
651 GGLGRSITSPTTLYDRYSSPTVSTTRRRLFENDSPSEGSTSGRIPPQPLV 700
701 NAVPVQNVPGETVSVTPVPGQTLVTMATATVTANNGQTVTIPVQGIANEN 750
751 GGITFFPVQVNVGGQAQAVAGSIQPLSAQALAGSLSSQQVTGTTLQVPGP 800
801 VAIQQISPGGQQQNPGQPLTSSSIRPRKTSSLALFFRKVYYLAGVRLRDL 850
851 CIKLDISDELRKKIWTCFEFSIIQCTELMMDRHLDQLLMCAIYVMAKVTK 900
901 EDRSFQNIMRCYRTQPQARSQVYRSVLIKGKRRNSGSSESRSHQNSPTEL 950
951 NTDRASRDSSPVMRSNSTLPVPQPSSAPPTPTRLTGASSDVEEEERGDLI 1000
1001 QFYNNIYRKQIQAFAMKYSQANAQTDTPPLSPYPFVRTGSPRRVQLSQSH 1050
1051 PIYISPHNNEAMPSPREKIFYYFSNSPSKRLREINSMIRTGETPTKKRGI 1100
1101 LLDDGSESPAKRICPENHSALLRRLQDVANDRGSQ 1135
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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