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

NucPred

Fetching Q96Q42 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MDSKKRSSTEAEGSKERGLVHIWQAGSFPITPERLPGWGGKTVLQAALGV    50
  51  KHGVLLTEDGEVYSFGTLPWRSGPVEICPSSPILENALVGQYVITVATGS   100
 101  FHSGAVTDNGVAYMWGENSAGQCAVANQQYVPEPNPVSIADSEASPLLAV   150
 151  RILQLACGEEHTLALSISREIWAWGTGCQLGLITTAFPVTKPQKVEHLAG   200
 201  RVVLQVACGAFHSLALVQCLPSQDLKPVPERCNQCSQLLITMTDKEDHVI   250
 251  ISDSHCCPLGVTLTESQAENHASTALSPSTETLDRQEEVFENTLVANDQS   300
 301  VATELNAVSAQITSSDAMSSQQNVMGTTEISSARNIPSYPDTQAVNEYLR   350
 351  KLSDHSVREDSEHGEKPVPSQPLLEEAIPNLHSPPTTSTSALNSLVVSCA   400
 401  SAVGVRVAATYEAGALSLKKVMNFYSTTPCETGAQAGSSAIGPEGLKDSR   450
 451  EEQVKQESMQGKKSSSLVDIREEETEGGSRRLSLPGLLSQVSPRLLRKAA   500
 501  RVKTRTVVLTPTYSGEADALLPSLRTEVWTWGKGKEGQLGHGDVLPRLQP   550
 551  LCVKCLDGKEVIHLEAGGYHSLALTAKSQVYSWGSNTFGQLGHSDFPTTV   600
 601  PRLAKISSENGVWSIAAGRDYSLFLVDTEDFQPGLYYSGRQDPTEGDNLP   650
 651  ENHSGSKTPVLLSCSKLGYISRVTAGKDSYLALVDKNIMGYIASLHELAT   700
 701  TERRFYSKLSDIKSQILRPLLSLENLGTTTTVQLLQEVASRFSKLCYLIG   750
 751  QHGASLSSFLHGVKEARSLVILKHSSLFLDSYTEYCTSITNFLVMGGFQL   800
 801  LAKPAIDFLNKNQELLQDLSEVNDENTQLMEILNTLFFLPIRRLHNYAKV   850
 851  LLKLATCFEVASPEYQKLQDSSSCYECLALHLGRKRKEAEYTLGFWKTFP   900
 901  GKMTDSLRKPERRLLCESSNRALSLQHAGRFSVNWFILFNDALVHAQFST   950
 951  HHVFPLATLWAEPLSEEAGGVNGLKITTPEEQFTLISSTPQEKTKWLRAI  1000
1001  SQAVDQALRGMSDLPPYGSGSSVQRQEPPISRSAKYTFYKDPRLKDATYD  1050
1051  GRWLSGKPHGRGVLKWPDGKMYSGMFRNGLEDGYGEYRIPNKAMNKEDHY  1100
1101  VGHWKEGKMCGQGVYSYASGEVFEGCFQDNMRHGHGLLRSGKLTSSSPSM  1150
1151  FIGQWVMDKKAGYGVFDDITRGEKYMGMWQDDVCQGNGVVVTQFGLYYEG  1200
1201  NFHLNKMMGNGVLLSEDDTIYEGEFSDDWTLSGKGTLTMPNGDYIEGYFS  1250
1251  GEWGSGIKITGTYFKPSLYESDKDRPKVFRKLGNLAVPADEKWKAVFDEC  1300
1301  WRQLGCEGPGQGEVWKAWDNIAVALTTSRRQHRDSPEILSRSQTQTLESL  1350
1351  EFIPQHVGAFSVEKYDDIRKYLIKACDTPLHPLGRLVETLVAVYRMTYVG  1400
1401  VGANRRLLQEAVKEIKSYLKRIFQLVRFLFPELPEEGSTIPLSAPLPTER  1450
1451  KSFCTGKSDSRSESPEPGYVVTSSGLLLPVLLPRLYPPLFMLYALDNDRE  1500
1501  EDIYWECVLRLNKQPDIALLGFLGVQRKFWPATLSILGESKKVLPTTKDA  1550
1551  CFASAVECLQQISTTFTPSDKLKVIQQTFEEISQSVLASLHEDFLWSMDD  1600
1601  LFPVFLYVVLRARIRNLGSEVHLIEDLMDPYLQHGEQGIMFTTLKACYYQ  1650
1651  IQREKLN                                             1657

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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