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

NucPred

Fetching Q10569 from www.uniprot.org...

The NucPred score for your sequence is 0.42 (see score help below)

   1  MYAVYKQAHPPTGLEFSMYCNFFNNSERNLVVAGTSQLYVYRLNRDSEAP    50
  51  TKNDRSTDGKAHREHREKLELVASFSFFGNVMSMASVQLAGAKRDALLLS   100
 101  FKDAKLSVVEYDPGTHDLKTLSLHYFEEPELRDGFVQNVHTPRVRVDPDG   150
 151  RCAAMLIYGTRLVVLPFRRESLAEEHEGLVGEGQRSSFLPSYIIDVRALD   200
 201  EKLLNIVDLQFLHGYYEPTLLILFEPNQTWPGRVAVRQDTCSIVAISLNI   250
 251  TQKVHPVIWSLTSLPFDCTQALAVPKPIGGVVIFAVNSLLYLNQSVPPYG   300
 301  VALNSLTTGTTAFPLRTQEGVRITLDCAQAAFISYDKMVISLKGGEIYVL   350
 351  TLITDGMRSVRAFHFDKAAASVLTTSMVTMEPGYLFLGSRLGNSLLLKYT   400
 401  EKLQEPPASTAREAADKEEPPSKKKRVDATTGWSGSKSVPQDEVDEIEVY   450
 451  GSEAQSGTQLATYSFEVCDSILNIGPCANAAMGEPAFLSEEFQNSPEPDL   500
 501  EIVVCSGYGKNGALSVLQKSIRPQVVTTFELPGCYDMWTVIAPVRKEQEE   550
 551  TLKGEGTEPEPGAPEAEDDGRRHGFLILSREDSTMILQTGQEIMELDASG   600
 601  FATQGPTVFAGNIGDNRYIVQVSPLGIRLLEGVNQLHFIPVDLGSPIVQC   650
 651  AVADPYVVIMSAEGHVTMFLLKNDSYGGRHHRLALHKPPLHHQSKVITLC   700
 701  VYRDVSGMFTTESRLGGVRDELGGRGGPEAEGQGAETSPTVDDEEEMLYG   750
 751  DSGSLFSPSKEEARRSSQPPADRDPAPFRAEPTHWCLLVRENGAMEIYQL   800
 801  PDWRLVFLVKNFPVGQRVLVDSSFGQPTTQGEARKEEATRQGELPLVKEV   850
 851  LLVALGSRQRRPYLLVHVDQELLIYEAFPHDSQLGQGNLKVRFKKVPHNI   900
 901  NFREKKPKPSKKKAEGGSTEEGTGPRGRVARFRYFEDIYGYSGVFICGPS   950
 951  PHWLLVTGRGALRLHPMGIDGPIDSFAPFHNINCPRGFLYFNRQGELRIS  1000
1001  VLPAYLSYDAPWPVRKIPLRCTAHYVAYHVESKVYAVATSTSTPCTRVPR  1050
1051  MTGEEKEFETIERDERYVHPQQEAFCIQLISPVSWEAIPNARIELEEWEH  1100
1101  VTCMKTVSLRSEETVSGLKGYVAAGTCLMQGEEVTCRGRILIMDVIEVVP  1150
1151  EPGQPLTKNKFKVLYEKEQKGPVTALCHCNGHLVSAIGQKIFLWSLRASE  1200
1201  LTGMAFIDTQLYIHQMISVKNFILAADVMKSISLLRYQEESKTLSLVSRD  1250
1251  AKPLEVYSVDFMVDNAQLGFLVSDRDRNLMVYMYLPEAKESFGGMRLLRR  1300
1301  ADFHVGAHVNTFWRTPCRGAAEGPSKKSVVWENKHITWFATLDGGIGLLL  1350
1351  PMQEKTYRRLLMLQNALTTMLPHHAGLNPRAFRMLHVDRRVLQNAVRNVL  1400
1401  DGELLNRYLYLSTMERGELAKKIGTTPDIILDDLLETDRVTAHF        1444

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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