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

NucPred

Fetching P87078 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MSESESDYFTDGSEDDFVPTSKKSTKKNASSKSKQPLGDATNSTVSSSRS    50
  51  STPKPTNASETYQKLSQLEHILKRPDTYIGSVEKTKTEMWCFDAETESMV   100
 101  FKEVTIVPGLYKIFDEILVNAADNKIRDPSMKNIRVKIDAENNIIEVMND   150
 151  GKGIPIEMHTKENMYIPELIFGNLLTSSNYDDDQKKVTGGRNGFGAKLCN   200
 201  IFSTQFEVETADLNMGKLYKQSWTNNMSNVSKPKITTLRTKKEYTKITFR   250
 251  PDLSKFDMDCLDNDLLSVLRRRVYDLCGTVKNCNIYLNDKRLNISSFKGY   300
 301  VEMYVKAIKERSPEPEPQDGTIKNFTTIVHEVFNDRWEVAFAVSDGSFNQ   350
 351  VSFVNSIATTSGGTHVKYVSDQIINKLVETLSKKEKGKKKLMIKPQEVRD   400
 401  NMFLFINCLIENPAFTSQTKEQLTTKVSQFGGKDKFVANDNLINRILKTS   450
 451  IVDKIRAIANANEDKALQKADGSRKSRIKGQVNLVDANKAGTKDGHNCTL   500
 501  ILTEGLSAMNLAVAGLSVVGRDYYGCFPLRGKLLNVREASADQISKNAEI   550
 551  NSLKQIIGLQHKKVYTAENIKSLRYGHIMIMTDQDQDGSHIKGLIINFLE   600
 601  TSFPGLLDIPGFLLEFITPIVKVTVKARGAGGKRVIPFYTMPEFEHWRDT   650
 651  EGKQCRWTQKYYKGLGTSTPMEAREYFTALDRHLKRFHALQGEDKDYIDL   700
 701  AFSKKKADERKEWLQGFLPGTHLDPEITEIPISDFINKEFILFSMSDNVR   750
 751  SIPSVLDGFKPGQRKVLYGCFKKKLRSEIKVAQLAGYVSENTGYHHGEQS   800
 801  LVQTIIGLAQNFVGSNNINVLKPNGSFGSRAAGGKDFSAARYIFTELSEI   850
 851  TRKIFNPLDDPLYTYVQDDEQTVEPEWYLPVLPMILVNGAEGIGTGWSTN   900
 901  IPSYNPKDLVTNIRRLMNGEELQEMTPWYKGWGGDLEPMGPQKFKVSGRI   950
 951  EQIDSNTVEITEIPVKTWTNNVKEFLLSGFGNEKTQPWIKDMEEHHTTSI  1000
1001  RFVVKLTDAEMQKSLRIGLLERFKLVSSLSLANMVAFDPMGRIKKYNDVL  1050
1051  EIIKDFYYVRLEYYQKRKDYMTDNLQNQLLMLSEQARFIKMIIEKQLSVA  1100
1101  NKKKKQLVALLEEHNFTKFSKDGKPIKSSEELLTGDDADEEEETQEQEGD  1150
1151  EDVGNTSVANIQEGEPEQAAHVPETIYSSYDYLLGMAIWSLTYERFMRIM  1200
1201  QQRDQKEAELNALLSKSAKDLWNQDLDEFLAEFDKFLLRDEQERESLASN  1250
1251  GKKKSTKRRAKATATKDQPNNKKVKVEPKEKKSTSAKPIVKKEASNEPQA  1300
1301  SSSSKPKEKDDILSFFSSSSSSAKKTTKPSGRATSNKEIETITLFSDDDD  1350
1351  DEDIFNLNSSSSTKVKKEAKSRSATPAAEKSKKSKSSGKQSILDELEDLE  1400
1401  ILGNFDKPEPKERRTRETASTTKRNTKKKPVIIDSDDEDEDEEDDIVMSD  1450
1451  GDDDDDFIVDE                                         1461

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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