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

NucPred

Fetching Q09427 from www.uniprot.org...

The NucPred score for your sequence is 0.37 (see score help below)

   1  MPLAFCGTENHSAAYRVDQGVLNNGCFVDALNVVPHVFLLFITFPILFIG    50
  51  WGSQSSKVHIHHSTWLHFPGHNLRWILTFILLFVLVCEIAEGILSDGVTE   100
 101  SRHLHLYMPAGMAFMAAITSVVYYHNIETSNFPKLLIALLIYWTLAFITK   150
 151  TIKFVKFYDHAIGFSQLRFCLTGLLVILYGMLLLVEVNVIRVRRYIFFKT   200
 201  PREVKPPEDLQDLGVRFLQPFVNLLSKGTYWWMNAFIKTAHKKPIDLRAI   250
 251  AKLPIAMRALTNYQRLCVAFDAQARKDTQSPQGARAIWRALCHAFGRRLI   300
 301  LSSTFRILADLLGFAGPLCIFGIVDHLGKENHVFQPKTQFLGVYFVSSQE   350
 351  FLGNAYVLAVLLFLALLLQRTFLQASYYVAIETGINLRGAIQTKIYNKIM   400
 401  HMSTSNLSMGEMTAGQICNLVAIDTNQLMWFFFLCPNLWTMPVQIIVGVI   450
 451  LLYYILGVSALIGAAVIILLAPVQYFVATKLSQAQRTTLEHSNERLKQTN   500
 501  EMLRGMKLLKLYAWESIFCSRVEVTRRKEMTSLRAFAVYTSISIFMNTAI   550
 551  PIAAVLITFVGHVSFFKESDLSPSVAFASLSLFHILVTPLFLLSSVVRST   600
 601  VKALVSVQKLSEFLSSAEIREEQCAPREPAPQGQAGKYQAVPLKVVNRKR   650
 651  PAREEVRDLLGPLQRLAPSMDGDADNFCVQIIGGFFTWTPDGIPTLSNIT   700
 701  IRIPRGQLTMIVGQVGCGKSSLLLATLGEMQKVSGAVFWNSNLPDSEGED   750
 751  PSSPERETAAGSDIRSRGPVAYASQKPWLLNATVEENITFESPFNKQRYK   800
 801  MVIEACSLQPDIDILPHGDQTQIGERGINLSGGQRQRISVARALYQQTNV   850
 851  VFLDDPFSALDVHLSDHLMQAGILELLRDDKRTVVLVTHKLQYLPHADWI   900
 901  IAMKDGTIQREGTLKDFQRSECQLFEHWKTLMNRQDQELEKETVMERKAS   950
 951  EPSQGLPRAMSSRDGLLLDEEEEEEEAAESEEDDNLSSVLHQRAKIPWRA  1000
1001  CTKYLSSAGILLLSLLVFSQLLKHMVLVAIDYWLAKWTDSALVLSPAARN  1050
1051  CSLSQECDLDQSVYAMVFTLLCSLGIVLCLVTSVTVEWTGLKVAKRLHRS  1100
1101  LLNRIILAPMRFFETTPLGSILNRFSSDCNTIDQHIPSTLECLSRSTLLC  1150
1151  VSALTVISYVTPVFLVALLPLAVVCYFIQKYFRVASRDLQQLDDTTQLPL  1200
1201  VSHFAETVEGLTTIRAFRYEARFQQKLLEYTDSNNIASLFLTAANRWLEV  1250
1251  CMEYIGACVVLIAAATSISNSLHRELSAGLVGLGLTYALMVSNYLNWMVR  1300
1301  NLADMEIQLGAVKRIHALLKTEAESYEGLLAPSLIPKNWPDQGKIQIQNL  1350
1351  SVRYDSSLKPVLKHVNTLISPGQKIGICGRTGSGKSSFSLAFFRMVDMFE  1400
1401  GRIIIDGIDIAKLPLHTLRSRLSIILQDPVLFSGTIRFNLDPEKKCSDST  1450
1451  LWEALEIAQLKLVVKALPGGLDAIITEGGENFSQGQRQLFCLARAFVRKT  1500
1501  SIFIMDEATASIDMATENILQKVVMTAFADRTVVTIAHRVHTILSADLVM  1550
1551  VLKRGAILEFDKPETLLSQKDSVFASFVRADK                    1582

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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