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

NucPred

Fetching Q03661 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MSKKKETFTPRANKLKLTTPRRKLKILSSLLDADEDSKMKDQHGYSRVHN    50
  51  DKYRVAKPTQHSTLHESISSRRSSHIHNKSLHEDSARALSWVDSLINRGK   100
 101  SILTTLEKEDALFERSLEEERQRFQLHDSLMNKYTGNSKSHQRLIDLRKS   150
 151  QYGTDTSFQNNDEIPLDSFISSPLPDAEDESSSNIDSDKDEDLEGKQSLI   200
 201  KDFDLENDEYELSEEEKNSDGQSSPSIMILSDEEYAEEGALQDVSNDEYA   250
 251  EEEGQVERKNIGQEQANVENATQISSSDSSEGQNYSEGVEMELEDDIDVE   300
 301  SDAEKDESQGAEGTEHSVDFSKYMQPRTDNTKIPVIEKYESDEHKVHQRY   350
 351  SEDGAFDFGSVNISVDDESEDEESQAESYSANAENVYHHNEHELDDKELI   400
 401  EDIESSDSESQSAQESEQGSEDDFEYKMKNEKSTSEETENTSESRDQGFA   450
 451  KDAYTKNKVEQQENDEEPEKDDIIRSSLDKNFHGNNNKSEYSENVLENET   500
 501  DPAIVERENQINDVEGYDVTGKSVESDLHEHSPDNLYDLAARAMLQFQQS   550
 551  RNSNCPQKEEQVSESYLGHSNGSNLSGRSLDESEEQIPLKDFTGENNNNL   600
 601  KTDRGDLSSSVEIEVEKVSEKKLDGSTEKELVPLSTDTTINNSSLGNEDS   650
 651  IYYSLDDADAISENLTDVPLMEIKTTPKYEVVISESVYSSTSYEDNTVAM   700
 701  PPQVEYTSPFMNDPFNSLNDDYEKKHDLLKSTLAALAPAFTKKDAEFVEA   750
 751  GVTKSCLTSTSGHTNIFHTSKETKQVSDLDESTENVTFENENTGDENKNQ   800
 801  SKNFPGVANSTDKSTEDNTDEKYFSAINYTNVTGDSSCEDIIETASNVEE   850
 851  NLRYCEKDMNEAEMSSGDECVKQNDDGSKTQISFSTDSPDNFQESNDNTE   900
 901  FSSTKYKVRNSDLEDDESLKKELTKAEVVDKLDEEESEDSYEQDYADPEP   950
 951  GNDEGSNENIVKGTKKDTLGIVEPENEKVNKVHEEETLFEANVSSSVNVQ  1000
1001  NKDMHTDVINQEAQANYEAGERKYYIQNTDTEEAHISIIERIDENAIGNN  1050
1051  MEIPERSCVEKTHNEVLFERRATTIENTKALENNTNMHDQVSQACSDSDR  1100
1101  DQDSTAEKNVEGSAKHNLDIRVSSSEIESVEPLKPESDRSNIFSSPIRVI  1150
1151  GAVVKGVGKVVDVAESFVKKIDVMDSESDDNVDIGDYNQDIFNKSNSTDA  1200
1201  SVNMKSVSSKERDSDEDEAVILGGVTAEAHNDNGNNSRVINIDPTTNGAY  1250
1251  EEDSEVFRQQVKDKENLHKSEEPLVEGLQSEQHFEKKDHSENEEEFDTIY  1300
1301  GDITSANIHSNAPDDIKRQQLLKNLSDLENYSQRLIEDSRRGKNQEESDE  1350
1351  VNTSRERDLTFEKSVNEKYAGAIEEDTFSELDISIQHPEHEEDLDLSNNQ  1400
1401  ERSIEELNSEPEEAELYELEIEGPTETAASSKMNDDERQRGNIPSTDLPS  1450
1451  DPPSDKEEVTDSYPYSNSENITAEKSAPTSPEVYEIFSDTPNEVPMEIND  1500
1501  EIPATTLEKHDKTNVTSVLDDRSEHLSSHDVDNEPHDNSINIKVNEGEEP  1550
1551  EHQAVDIPVKVEVKEEQEEMPSKSVLEEQKPSMELINDKSSPENNNDEET  1600
1601  NREKDKTKAKKKSRKRNYNSRRRKRKITEGSSAASNTKRRRGHEPKSRGQ  1650
1651  NTHPSVDK                                            1658

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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