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

NucPred

Fetching Q91274 from www.uniprot.org...

The NucPred score for your sequence is 0.56 (see score help below)

   1  MGKAMLKLCITLMVLVFSGTAESKGVMRREDESFPHLKSRLCGGLNGLGE    50
  51  DAYRSHCVVYYTKRMGVVSLDHVEELANHCLRIVKQCCAEGAADDCLQTE   100
 101  LAAVQEQVCTRMSEAKDVPLVGRCCALAGSERHDCFHHAGGVAEGEGAWP   150
 151  HALPVTSPPEYDSVTVCALHATANARLYDTLLWEFSRRYPSASDSHLIAL   200
 201  ANEFITGLTTCCLVEEEHGACLATLREDFKHKLTEASHKSQNLCKALKSL   250
 251  GKEKFEDRIIVRFTQRAPQAPFELIQKLAHRFEVLAEKCCELGHSDRCLV   300
 301  EERYTVDDELCLEQSFVATCPRLSSCCSLSGSSRAQCLETVPVLETSDKA   350
 351  SPATPTLPISEQCTLWAGKPVEFHKRVVWQISHRYPTTGVAQVEALAHHY   400
 401  LEHLTICCASEDKDTCIATEVAEFKSEVEKVHTKSDWWCRMSDLLGTDRF   450
 451  NLLLIVTYSQRVPQATFEQVEEISHHFALITRKCCSHRKNGSCFLEERYA   500
 501  LHDAICRDEAWLSGLAEVSRCCAMDGRARILCFDELSSHLNASVEERPEL   550
 551  CSTSLCSKYHDLGFEFKQRVAYGFGQRFPKAAMGQMRDLISKYLAMVQRC   600
 601  CDAMSDFKMDVEEVELRAHRLCLDAHQLGEEKLADRIMIGLAQRISVASF   650
 651  VNISSVALHFAQSVIKCCDADHEKTCFMEQEFALEDQVCSDSEALSHIPS   700
 701  VSRCCELHPFDRSVCFHSLRSTQASTLASTHVAVGKDDSLPGHVEECQAF   750
 751  ASGNHSLTDQVMFEFARRHPRASVSQVESLARLYSELARACCALTDADQE   800
 801  SCLHTARSQARQEALKSLQRSERICNTLSAIGKEKFEDRIVIALSQKATD   850
 851  ASFEQILEIANRMSRGLARCCEQGNNVGCLMDHRHALHEAICSTPDGSLP   900
 901  QSVAACCNTSNTSTTTSTTTSTTTSTTTSTTTSTTSTTTAAEIRDSCFDN   950
 951  LQANVSRAHAPFYSNSQLCLMKLRTPHRFLERFLWEFGRRHPQAALSQVE  1000
1001  ELAEMYVKMTDSCCGKLHSKSCFTEQRHTIHMEIRHAYAEVQHICGSLHS  1050
1051  RGEETFIQREVTLLSQKAPNASFEKVSQLARHFLSLAKKCCAPDHAAGCF  1100
1101  LEEPYAIHDEVCRDDEVVDQVGGLATCCRMSGTSRAKCLAQLPRDLGRHG  1150
1151  NRETPEFDELKICELRRDNPAVLMEKILYEFGRRHSDSAVSEVKNFAQKF  1200
1201  SHSVTECCTSEKTHECFVEKRAAIEKVIKDEEAKGNLTCQRLKAQGVEHF  1250
1251  EQLVILNFARAAKSLPMEKVVEFAHRFTRIAGQCCEHDTHCLIDESFHLH  1300
1301  AEMCGDHGYIMAHPGVANCCKSDVSEQGTCFKIHEDVHHAEEILSKDVSP  1350
1351  AHPTAERVCLRYRQFPEKFINLALFELVHRLPLLESSVLRRKALAYTGFT  1400
1401  DDCCRAVDKTACFTEKLEAIKSS                             1423

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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