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

NucPred

Fetching Q13219 from www.uniprot.org...

The NucPred score for your sequence is 0.67 (see score help below)

   1  MRLWSWVLHLGLLSAALGCGLAERPRRARRDPRAGRPPRPAAGPATCATR    50
  51  AARGRRASPPPPPPPGGAWEAVRVPRRRQQREARGATEEPSPPSRALYFS   100
 101  GRGEQLRLRADLELPRDAFTLQVWLRAEGGQRSPAVITGLYDKCSYISRD   150
 151  RGWVVGIHTISDQDNKDPRYFFSLKTDRARQVTTINAHRSYLPGQWVYLA   200
 201  ATYDGQFMKLYVNGAQVATSGEQVGGIFSPLTQKCKVLMLGGSALNHNYR   250
 251  GYIEHFSLWKVARTQREILSDMETHGAHTALPQLLLQENWDNVKHAWSPM   300
 301  KDGSSPKVEFSNAHGFLLDTSLEPPLCGQTLCDNTEVIASYNQLSSFRQP   350
 351  KVVRYRVVNLYEDDHKNPTVTREQVDFQHHQLAEAFKQYNISWELDVLEV   400
 401  SNSSLRRRLILANCDISKIGDENCDPECNHTLTGHDGGDCRHLRHPAFVK   450
 451  KQHNGVCDMDCNYERFNFDGGECCDPEITNVTQTCFDPDSPHRAYLDVNE   500
 501  LKNILKLDGSTHLNIFFAKSSEEELAGVATWPWDKEALMHLGGIVLNPSF   550
 551  YGMPGHTHTMIHEIGHSLGLYHVFRGISEIQSCSDPCMETEPSFETGDLC   600
 601  NDTNPAPKHKSCGDPGPGNDTCGFHSFFNTPYNNFMSYADDDCTDSFTPN   650
 651  QVARMHCYLDLVYQGWQPSRKPAPVALAPQVLGHTTDSVTLEWFPPIDGH   700
 701  FFERELGSACHLCLEGRILVQYASNASSPMPCSPSGHWSPREAEGHPDVE   750
 751  QPCKSSVRTWSPNSAVNPHTVPPACPEPQGCYLELEFLYPLVPESLTIWV   800
 801  TFVSTDWDSSGAVNDIKLLAVSGKNISLGPQNVFCDVPLTIRLWDVGEEV   850
 851  YGIQIYTLDEHLEIDAAMLTSTADTPLCLQCKPLKYKVVRDPPLQMDVAS   900
 901  ILHLNRKFVDMDLNLGSVYQYWVITISGTEESEPSPAVTYIHGSGYCGDG   950
 951  IIQKDQGEQCDDMNKINGDGCSLFCRQEVSFNCIDEPSRCYFHDGDGVCE  1000
1001  EFEQKTSIKDCGVYTPQGFLDQWASNASVSHQDQQCPGWVIIGQPAASQV  1050
1051  CRTKVIDLSEGISQHAWYPCTISYPYSQLAQTTFWLRAYFSQPMVAAAVI  1100
1101  VHLVTDGTYYGDQKQETISVQLLDTKDQSHDLGLHVLSCRNNPLIIPVVH  1150
1151  DLSQPFYHSQAVRVSFSSPLVAISGVALRSFDNFDPVTLSSCQRGETYSP  1200
1201  AEQSCVHFACEKTDCPELAVENASLNCSSSDRYHGAQCTVSCRTGYVLQI  1250
1251  RRDDELIKSQTGPSVTVTCTEGKWNKQVACEPVDCSIPDHHQVYAASFSC  1300
1301  PEGTTFGSQCSFQCRHPAQLKGNNSLLTCMEDGLWSFPEALCELMCLAPP  1350
1351  PVPNADLQTARCRENKHKVGSFCKYKCKPGYHVPGSSRKSKKRAFKTQCT  1400
1401  QDGSWQEGACVPVTCDPPPPKFHGLYQCTNGFQFNSECRIKCEDSDASQG  1450
1451  LGSNVIHCRKDGTWNGSFHVCQEMQGQCSVPNELNSNLKLQCPDGYAIGS  1500
1501  ECATSCLDHNSESIILPMNVTVRDIPHWLNPTRVERVVCTAGLKWYPHPA  1550
1551  LIHCVKGCEPFMGDNYCDAINNRAFCNYDGGDCCTSTVKTKKVTPFPMSC  1600
1601  DLQGDCACRDPQAQEHSRKDLRGYSHG                         1627

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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