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

NucPred

Fetching O74298 from www.uniprot.org...

The NucPred score for your sequence is 0.23 (see score help below)

   1  MAVGTASLQDRLETWAQRLKNLTVSPLTRDYPDTQKTDSKRVIEAFESLQ    50
  51  LPKAKLTGSSSSFIAFLTAFIILVARLTGDEDIAVGTNSNEDGRAFVIRV   100
 101  PIDTSESFAQLYAKVDKAYKEGSSQIVPLGSLRSYIQEKSKSERTPVLFR   150
 151  FAAYDAPASSQDYPANTFDTTDLVVNVAPGSAEVELGAYYNQRLFSSARI   200
 201  AFILKQLASIASNAAANPDEAIGRIDLMTEDQRALLPDPTCNLNWSNFRG   250
 251  AIHDIFTANAERHPEKLCVVETQSSSSPHREFTYRQINEASNILGHHLVR   300
 301  SGIQRGEVVMVYAYRGVDLVVAVMGILKAGATFSVIDPAYPPERQNIYLD   350
 351  VARPRALVNIAKATKDAGELSDIVRTFIDENLELRTEIPALALLDDGTLA   400
 401  GGSINGQDVFANDVALKSKPTGVVVGPDSIPTLSFTSGSEGRPKGVRGRH   450
 451  FSLAYYFPWMSETFKLTPDEKFTMLSGIAHDPIQRDIFTPLFLGAQLLVP   500
 501  AREDIQNEKLAEWIEKYGATITHLTPAMGQILVGGASAQFPALHHAFFVG   550
 551  DILIKRDCRSLQGLAPNVSIVNMYGTTETQRAVSYYEIPSYASNEGYLNN   600
 601  MKDVIMAGRGMLDVQMLVVNRYDPTRLCAIGEVGEIYVRAGGLAEGYLGS   650
 651  PELSAKKFLNNWFVNPEIWAEKDQAESRNEPWRQFYVGPRDRLYRSGDLG   700
 701  RYTPSGDVECSGRADDQVKIRGFRIELGEIDTHLSQHPLVRENVTLVRRD   750
 751  KDEEPTLVSYFVPDMNKWASWLESKGLKDDDSDSEGMVGLLRRFRPLRDD   800
 801  AREHLRTKLPTYAVPTVIIPLKRMPLNPNGKIDKPALPFPDTAELSAAAP   850
 851  RRASSALQALSETEQTLAQVWAKLIPNVTSRMIGPDDSFFDLGGHSILAQ   900
 901  QMFFELRRKWRVIDISMNAIFRSPTLKGFASEIDRLLAMESFATSDDKTL   950
 951  AVQAANEPDDEYSKDAVQLVNELPKTFPQRTEAMLTSEPTVFLTGATGFL  1000
1001  GAHILRDLLTRKSPSTKVVALVRAKTEELALERLRSTCRAYGFWDEAWTA  1050
1051  KLQAVCGDLGKPQFGLSQSVWDDLTNRVDAVIHNGALVHWVYPYATLRPA  1100
1101  NVMGTIDALKLCASGKAKQFAFVSSTSALDKDRYVQESERIIAAGGNGIS  1150
1151  EDDDMEGSRVGLGTGYGQSKWAGEYLVKEAGRRGLRGTIVRSGYVLGDSV  1200
1201  TGTTNTDDFLIRMLKGCIQIGLRPNIFNTVNMVPVDHVARIVIATAFHPP  1250
1251  ATGVNVAHVTGHPRLRFNQFLGALELYGYNVPQVDYVPWSTSLEQYVNDG  1300
1301  EHNDKESQHALMPLYHFVTSDLPSNTKAPELDDVNAATALRADATWSGVD  1350
1351  ASAGAGVTEELVGLYASYLVQTGFLPAPTVAGARPLPAAQISEEQKKTLL  1400
1401  SVGGRGGTS                                           1409

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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