SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q9UN72 from www.uniprot.org...

The NucPred score for your sequence is 0.26 (see score help below)

   1  MVCPNGYDPGGRHLLLFIIILAAWEAGRGQLHYSVPEEAKHGNFVGRIAQ    50
51 DLGLELAELVPRLFRAVCKFRGDLLEVNLQNGILFVNSRIDREELCGRSA 100
101 ECSIHLEVIVERPLQVFHVDVEVKDINDNPPVFPATQRNLFIAESRPLDS 150
151 RFPLEGASDADIGENALLTYRLSPNEYFFLDVPTSNQQVKPLGLVLRKLL 200
201 DREETPELHLLLTATDGGKPELTGTVQLLITVLDNNDNAPVFDRTLYTVK 250
251 LPENVSIGTLVIHPNASDLDEGLNGDIIYSFSSDVSPDIKSKFHMDPLSG 300
301 AITVIGHMDFEESRAHKIPVEAVDKGFPPLAGHCTVLVEVVDVNDNAPQL 350
351 TLTSLSLPIPEDAQPGTVITLISVFDRDFGVNGQVTCSLTPRVPFKLVST 400
401 FKNYYSLVLDSALDRESVSAYELVVTARDGGSPSLWATASVSVEVADVND 450
451 NAPAFAQPEYTVFVKENNPPGCHIFTVSAGDADAQKNALVSYSLVELRVG 500
501 ERALSSYVSVHAESGKVYALQPLDHEELELLQFQVSARDAGVPPLGSNVT 550
551 LQVFVLDENDNAPALLAPRVGGTGGAVRELVPRSVGAGHVVAKVRAVDAD 600
601 SGYNAWLSYELQPVAAGASIPFRVGLYTGEISTTRALDETDAPRHRLLVL 650
651 VKDHGEPSLTATATVLVSLVESGQAPKASSRASLGIAGPETELVDVNVYL 700
701 IIAICAVSSLLVLTLLLYTALRCSAPSSEGACSLVKPTLVCSSAVGSWSF 750
751 SQQRRQRVCSGEGPPKTDLMAFSPSLPQGPSSTDNPRQPNPDWRYSASLR 800
801 AGMHSSVHLEEAGILRAGPGGPDQQWPTVSSATPEPEAGEVSPPVGAGVN 850
851 SNSWTFKYGPGNPKQSGPGELPDKFIIPGSPAIISIRQEPTNSQIDKSDF 900
901 ITFGKKEETKKKKKKKKGNKTQEKKEKGNSTTDNSDQ 937

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

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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