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

NucPred

Fetching Q28021 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MSRPPPTGKMPGAPEAVSGDGAGASRQRKLEALIRDPRSPINVESLLDGL    50
  51  NPLVLDLDFPALRKNKNIDNFLNRYEKIVKKIRGLQMKAEDYDVVKVIGR   100
 101  GAFGEVQLVRHKASQKVYAMKLLSKFEMIKRSDSAFFWEERDIMAFANSP   150
 151  WVVQLFCAFQDDKYLYMVMEYMPGGDLVNLMSNYDVPEKWAKFYTAEVVL   200
 201  ALDAIHSMGLIHRDVKPDNMLLDKHGHLKLADFGTCMKMDETGMVHCDTA   250
 251  VGTPDYISPEVLKSQGGDGYYGRECDWWSVGVFLFEMLVGDTPFYADSLV   300
 301  GTYSKIMDHKNSLCFPEDAEISKHAKNLICAFLTDREVRLGRNGVEEIKQ   350
 351  HPFFKNDQWNWDNIRETAAPVVPELSSDIDSSNFDDIEDDKGDVETFPIP   400
 401  KAFVGNQLPFIGFTYYRENLLLSDSPSCKENDSIQSRKNEESQEIQKKLY   450
 451  TLEEHLSTEIQAKEELEQKCKSVNTRLEKVAKELEEEITLRKNVESTLRQ   500
 501  LEREKALLQHKNAEYQRKADHEADKKRNLENDVNSLKDQLEDLKKRNQNS   550
 551  QISTEKVNQLQRQLDETNALLRTESDTAARLRKTQAESSKQIQQLESNNR   600
 601  DLQDKNCLLETAKLKLEKEFINLQSVLESERRDRTHGSEIINDLQGRISG   650
 651  LEEDVKNGKILLAKVELEKRQLQERFTDLEKEKNNMEIDMTYQLKVIQQS   700
 701  LEQEETEHKATKARLADKNKIYESIEEAKSEAMKEMEKKLSEERTLKQKV   750
 751  ENLLLEAEKRCSILDCDLKQSQQKINELLKQKDVLNEDVRNLTLKIEQET   800
 801  QKRCLTQNDLKMQTQQVNTLKMSEKQLKQENNHLLEMKMSLEKQNAELRK   850
 851  ERQDADGQMKELQDQLEAEQYFSTLYKTQVRELKEECEEKTKLCKELQQK   900
 901  KQELQDERDSLAAQLEITLTKADSEQLARSIAEEQYSDLEKEKIMKELEI   950
 951  KEMMARHKQELTEKDATIASLEETNRTLTSDVANLANEKEELNNKLKEAQ  1000
1001  EQLSRLKDEEISAAAIKAQFEKQLLTERTLKTQAVNKLAEIMNRKEPVKR  1050
1051  GNDTDVRRKEKENRKLHMELKSEREKLTQQMIKYQKELNEMQAQIAEESQ  1100
1101  IRIELQMTLDSKDSDIEQLRSQLQALHIGLDSSSIGSGPGDTEADDGFPE  1150
1151  SRLEGWLSLPVRNNTKKFGWVKKYVIVSSKKILFYDSEQDKEQSNPYMVL  1200
1201  DIDKLFHVRPVTQTDVYRADAKEIPRIFQILYANEGESKKEQEFPVEPVG  1250
1251  EKSNYICHKGHEFIPTLYHFPTNCEACMKPLWHMFKPPPALECRRCHIKC  1300
1301  HKDHMDKKEEIIAPCKVYYDISSAKNLLLLANSTEEQQKWVSRLVKKIPK  1350
1351  KPPAPDPFARSSPRTSMKIQQNQSIRRPSRQLAPNKPS              1388

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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