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

NucPred

Fetching P36619 from www.uniprot.org...

The NucPred score for your sequence is 0.21 (see score help below)

   1  MSLHSKKSTSTVKDNEHSLDLSIKSIPSNEKNFSTEKSENEASESHVVDV    50
  51  VKDPFEQYTPEEQEILYKQINDTPAKLSGYPRILSYADKWDIMLQLAGTI   100
 101  TGIGAGLGMPLMSLVSGQLAQAFTDLASGKGASSFQHTVDHFCLYFIYIA   150
 151  IGVFGCSYIYTVTFIIAGERIARRIRQDYLHAILSQNIGYFDRLGAGEIT   200
 201  TRITTDTNFIQDGLGEKVGLVFFAIATFVSGFVIAFIRHWKFTLILSSMF   250
 251  PAICGGIGLGVPFITKNTKGQIAVVAESSTFVEEVFSNIRNAFAFGTQDI   300
 301  LAKLYNKYLITAQRFGINKAIAMGLMVGWMFFVAYGVYGLAFWEGGRLLH   350
 351  AGDLDVSKLIGCFFAVLIASYSLANISPKMQSFVSCASAAKKIFDTIDRV   400
 401  SPINAFTPTGDVVKDIKGEIELKNIRFVYPTRPEVLVLDNFSLVCPSGKI   450
 451  TALVGASGSGKSTIIGLVERFYDPIGGQVFLDGKDLRTLNVASLRNQISL   500
 501  VQQEPVLFATTVFENITYGLPDTIKGTLSKEELERRVYDAAKLANAYDFI   550
 551  MTLPEQFSTNVGQRGFLMSGGQKQRIAIARAVISDPKILLLDEATSALDS   600
 601  KSEVLVQKALDNASRSRTTIVIAHRLSTIRNADNIVVVNAGKIVEQGSHN   650
 651  ELLDLNGAYARLVEAQKLSGGEKDQEMVEEELEDAPREIPITSFGDDDED   700
 701  NDMASLEAPMMSHNTDTDTLNNKLNEKDNVVFEDKTLQHVASEIVPNLPP   750
 751  ADVGELNEEPKKSKKSKKNNHEINSLTALWFIHSFVRTMIEIICLLIGIL   800
 801  ASMICGAAYPVQAAVFARFLNIFTDLSSTDFLHKVNVFAVYWLILAIVQF   850
 851  FAYAISNFAMTYAMEAVLQRIRYHLFRTLLRQDVEFFDRSENTVGAITTS   900
 901  LSTKIQSLEGLSGPTLGTFFQILTNIISVTILSLATGWKLGLVTLSTSPV   950
 951  IITAGYYRVRALDQVQEKLSAAYKESAAFACESTSAIRTVASLNREENVF  1000
1001  AEYCDSLIKPGRESAIASLKSGLFFSAAQGVTFLINALTFWYGSTLMRKG  1050
1051  EYNIVQFYTCFIAIVFGIQQAGQFFGYSADVTKAKAAAGEIKYLSESKPK  1100
1101  IDTWSTEGKKVESLQSAAIEFRQVEFSYPTRRHIKVLRGLNLTVKPGQFV  1150
1151  AFVGSSGCGKSTTIGLIERFYDCDNGAVLVDGVNVRDYNINDYRKQIALV  1200
1201  SQEPTLYQGTVRENIVLGASKDVSEEEMIEACKKANIHEFILGLPNGYNT  1250
1251  LCGQKGSSLSGGQKQRIAIARALIRNPKILLLDEATSALDSHSEKVVQEA  1300
1301  LNAASQGRTTVAIAHRLSSIQDADCIFVFDGGVIAEAGTHAELVKQRGRY  1350
1351  YELVVEQGLNKA                                        1362

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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