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

NucPred

Fetching Q8GU88 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MDIVRMGSVASGGGSVRRTASSWRGTSGRSDAFGRSVREEDDEEALKWAA    50
  51  IEKLPTYDRMRKGILTAGGVEEVDIGGLGLQERRNLIERLVRTAEEDNER   100
 101  FLLKLRDRMERVGIDNPTIEVRFENLSIDAEAYVGNRGIPTFTNFFSNKI   150
 151  MDVLSAMRIVSSGKRPISILHDISGIIRPGRMSLLLGPPGSGKTSLLLAL   200
 201  AGKLDSTLKVSGRVTYNGHDMDEFVPQRTSAYIGQHDLHIGEMTVRETLA   250
 251  FSARCQGVGTRYDMLTELSRREKEASIKPDPDIDVYMKAISVEGQESVVT   300
 301  DYILKILGLEICADTMVGDAMIRGISGGQKKRVTTGEMLVGPAKALFMDE   350
 351  ISTGLDSSTTYQIVNSLRQSVHILGGTALIALLQPAPETYDLFDDIVLLS   400
 401  EGQIVYQGPRENILEFFEAMGFKCPERKGVADFLQEVTSRKDQHQYWCRR   450
 451  DEPYRYISVNDFSEAFKEFHVGRNLGSELRVPFDRTRNHPAALTTSRYGI   500
 501  SKMELTKACFSREWLLMKRNSFVYIFKILQLIILGSIGMTVFLRTKMHRR   550
 551  SVEDGAIFLGAMFLGLVTHLFNGFAELAMSIAKLPIFYKQRDLLFYPSWA   600
 601  YALPTWVLKIPISFLECAVWICMTYYVMGFDPNIERFFRHYVLLVLISQM   650
 651  ASGLFRLLAALGREMVVADTFGSFAQLILLVLGGFLISRENIKKWWIWGY   700
 701  WSSPLMYAQNAIAVNEFLGHSWNKVVDPTQSNDTLGVQVLKVRGIFVDAN   750
 751  WYWIGVGALLGYIMLFNILFILFLEWLDPLGKGQAVVSEEELREKHVNRT   800
 801  GENVELLTLGTDSQNSPSDANAGRGEITGADTRKRGMVLPFTPLSITFDN   850
 851  IRYSVDMPQEMKDKGVTEDRLLLLKGVSGAFRPGVLTALMGVSGAGKTTL   900
 901  MDVLAGRKTGGYIEGDISISGYPKKQETFARIAGYCEQNDIHSPHVTVYE   950
 951  SLLYSAWLRLPSEVDSEARKMFVEEVMELVELTSLRGALVGLPGVNGLST  1000
1001  EQRKRLTIAVELVANPSIIFMDEPTSGLDARAAAIVMRTVRNTVDTGRTV  1050
1051  VCTIHQPSIDIFEAFDELFLMKRGGEEIYVGPLGHNSCHLINYFEGIQGV  1100
1101  RKIKDGYNPATWMLEVTTLAQEDILGINFAEVYRNSDLYQRNKTLISELS  1150
1151  TPPPGSTDLHFPTQFSQPFFTQCMACLWKQHKSYWRNPSYTATRIFFTTV  1200
1201  IALIFGTIFLNLGKKINKRLDLFNSLGSMYAAVLFIGIQNGQTVQPIVDV  1250
1251  ERTVFYREKAAGMYSALPYAFAQVLIEIPHIFLQTVVYGLIVYSLIGFDW  1300
1301  TVEKFFWYMFFMFFTFMYFTFYGMMAVAMTPNSDIAAIVSTAFYCIWNIF  1350
1351  AGFLIPRPRIPIWWRWYSWACPVAWTLYGLVASQYGDITNSTLEDGEVVQ  1400
1401  DYIRRYFGFRHDYLGYVATAVVGFAALFAFVFAFSIKVFNFQRR        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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