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

NucPred

Fetching Q00799 from www.uniprot.org...

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

   1  MEKNVLWVIFYNFLVILLASCNDSNRSKSNSLKSESKSLPTYANLMRNGQ    50
  51  DKYNNAKTEDNIGNQINNDNNHNGYNDNRINSEYPKTSHLQHSPSLVHLN   100
 101  DHKFTTKPSRHSYVQRNSIYKRNTNNNMENTNNELHVVPNFFIQEKKAAP   150
 151  QKPSVQNTPTATQIVYNNLDYLNAFDDTNNIISAFKPHHPIIYYFKQLEH   200
 201  FANSYYDLRNKIKDYFALPMKQASDVVEKNVKDCLQNINESRILMTQLEN   250
 251  PQNYNDISDKYDEKVKEYKKKIEDMQICLKDSYIKNFKAIMSANLKMNLA   300
 301  LNGIYIHWWYLTCSTKTYDDIVKEYAIEINDFDEKKSISFMDNMKKIHKS   350
 351  AIDTLKKMKAELNTSLDSKRTEFIIGEIGHMIEKFNLHLTKIRYASAFIK   400
 401  SIPLQKVESDIYRVELKTLFYVAAKHYADFKFSLEHLKMFENLSKSKEKM   450
 451  LYSTFEKLEGDLLNKINTLMGSEQSTSDLTSIIADSEKIIKSAESLINSS   500
 501  SEEIAKYALDSNEKINEIKKNYDQNILKVREFINKSNGLITSVKGTSQLS   550
 551  ESDKQQIETKIEEIKKKKKDILERGKEFINIMNEIKKKKKSNSSNSSTNS   600
 601  KEFTDKLKELETEFEGLNKTVKGYLQEIEDIKVKENEDRSLKNQIEQHLK   650
 651  YTSDNRDNVKTLISKNDEIQKYIEKIEKLINDAPSGKDKFTTEKTNLQNK   700
 701  VKKIIDEFHKEDLQLLLNSLSKFYEEHQKLYNEASTIEKIKDLHQKTKEE   750
 751  YEKLEKMKFSNFGQILDKLNTELDNLKTLEKNIVEEQTNYINKVMSDSLT   800
 801  NLTAEVDNLRSALDGYRADETELKTYKNRINERKEKFLSTLKEQEDDIPD   850
 851  GKNIYEEYNNHKNVMVNKEHKISSDINQCNENIIKAEKNLETFNTLVQTL   900
 901  DAHTGKKDQKVHDLLQKFKTNLEKLNLNELESGFKSLNGSASTTNKQIEN   950
 951  IRKNIDTIKSLNFAKNSSESSKLSLENIIKNKADLIKKLDQHTQEIEKHT  1000
1001  FIENEEMSPLLSVIKKEKNRVESDMSEELIKQLNTKINAILEYYNKSKDR  1050
1051  FNGDDETNLEELDDFKKQCQDAQQEIKKLTTNYNVLDNGINVIIKEQHEK  1100
1101  VIILSENHITEKDKKINEKIQQNVNSLNEMKTKLGLLKINEDIKNSRDTT  1150
1151  IKSKIQEFEKKVQTIFGSIDVANKKIDAIKKEHDVNKDEFDKEKVKDTSF  1200
1201  DEKKKSIEKAYEKMGNTLKELEKMDDEKNIEKEVEEAQIQYKRIFIDHDV  1250
1251  NLMNDEVEKSKIVMEKIELYKKEIDEIKQKTNEYKQGDTSNFYYTEQYNS  1300
1301  ATQSKAKIEQFINIATTKKGTSDTSQDINELESIKEEVHKNLQLVKQESN  1350
1351  SMEEMRKQILSMKDLLILNNSETIAKEISNNTQNALGFRENAKTKLNKTD  1400
1401  ELLQRVAAMIEEAKAHKNNIDIALEDAQIDTEVSKIEQINREIMNKKDEI  1450
1451  KSYLSEIKEYKDKCTTEISNSKRGKDKIEFLEKFKPNEESNSNKVNINEI  1500
1501  NENIRNSEQYLKDIEDAEKQASTKVELFHKHETTISNIFKESEILGVETK  1550
1551  SQKKINKAEDIMKEIERHNSEIQTQVKGFQENLNKLNEPHNYDNAEDELN  1600
1601  NDKSTNAKVLIETNLESVKHNLSEITNIKQGGEKIYSKAKDIMQKIKATS  1650
1651  ENTAEKTLEKVKDDQSNYVNYLNQITTERNLIVTEKNRLNGIDSTITNIE  1700
1701  GALKESKGNYEIGFLEKLEEIGKNRKLKVDITKKSINSTVGNFSSLFNNF  1750
1751  DLNQYDFNKNINDYENKMGEIYNEFEGSLNKISENLRNASENTSDYNSAK  1800
1801  TLRLEAQKEKVNLLNKEEEANKYLRDVKKVESFRFIFNMKESLDKINEMI  1850
1851  KKEQLTVNEGHGNVKQLVENIKELVDENNLSDILKQATGKNEEIQKITHS  1900
1901  TLKNKAKTILGHVDTSAKYVGIKITPELALTELLGDAKLKTAQELKFESK  1950
1951  NNVVLETENMSKNTNELDVHKNIQDAYKVALEILAHSDEIDTKQKDSSKL  2000
2001  IEMGNQIYLKVVLINQYKNKISSIKSKEEAVSVKIGNVSKKHSELSKITC  2050
2051  SDKSYDNIIALEKQTELQNLRNSFTQEKTNTNSDSKLEKIKTDFESLKNA  2100
2101  LKTLEGEVNALKASSDNHEHVQSKSEPVNPALSEIEKEETDIDSLNTALD  2150
2151  ELLKKGRTCEVSRYKLIKDTVTKEISDDTELINTIEKNVKAYLAYIKKNY  2200
2201  EDTVQDVLTLNEHFNTKQVSNHEPTNFDKSNKSSEELTKAVTDSKTIISK  2250
2251  LKGVIIEVNENTEMNTIESSAKEIEALYNELKNKKTSLNEIYQTSNEVKL  2300
2301  QEMKSNADKYIDVSKIFNTVLDTQKSNIVTNQHSINNVKDKLKGKLQELI  2350
2351  DADSSFTLESIKKFNEIYSHIKTNIGELEQLQQTNKSEHDNVAKHKEKIV  2400
2401  HLINRVESLKGDVKNHDDDQYMKKLNASLLNDNIKNTNSINISDEELKKL  2450
2451  LKKVEENDQLCKNNNTQNFISDIMKRVEDLNRRFTENLPEKEKLHQIENN  2500
2501  YNEISSIFSEINLQDVDEFVAKIHKQIDAEKASVNNVREAEKIRTAIQNV  2550
2551  TSYDTEIISRLSEMNNVLERITTRKTKMDQLLKSLSPDNTSLNLNARTHV  2600
2601  RKSEDIIKQLNSHIGEITELNTYAHEVMTYLENELNKLLKQLEIERAKLE  2650
2651  TKTSPSGMKAKEEKVPPKETENRAQDNLASVPQKTLEDNTQQMPENSVQD  2700
2701  NLASVPQKTLEDNTHQMPENRVQEDSISAPQEQVEYSTLAVPENDETTEE  2750
2751  ESEHDDAHDDTHDDTHDDTHDDTHDDTHDDTHDDTHDESQTGRDSTAKEA  2800
2801  IGKTRLAGAVIIAMSVLSGFIIIVFKDKDEEEKDHNEHGYNEAFGEHDEY  2850
2851  NMHDKEEVIEVCFNEED                                   2867

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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