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

NucPred

Fetching Q09428 from www.uniprot.org...

The NucPred score for your sequence is 0.44 (see score help below)

   1  MPLAFCGSENHSAAYRVDQGVLNNGCFVDALNVVPHVFLLFITFPILFIG    50
  51  WGSQSSKVHIHHSTWLHFPGHNLRWILTFMLLFVLVCEIAEGILSDGVTE   100
 101  SHHLHLYMPAGMAFMAAVTSVVYYHNIETSNFPKLLIALLVYWTLAFITK   150
 151  TIKFVKFLDHAIGFSQLRFCLTGLLVILYGMLLLVEVNVIRVRRYIFFKT   200
 201  PREVKPPEDLQDLGVRFLQPFVNLLSKGTYWWMNAFIKTAHKKPIDLRAI   250
 251  GKLPIAMRALTNYQRLCEAFDAQVRKDIQGTQGARAIWQALSHAFGRRLV   300
 301  LSSTFRILADLLGFAGPLCIFGIVDHLGKENDVFQPKTQFLGVYFVSSQE   350
 351  FLANAYVLAVLLFLALLLQRTFLQASYYVAIETGINLRGAIQTKIYNKIM   400
 401  HLSTSNLSMGEMTAGQICNLVAIDTNQLMWFFFLCPNLWAMPVQIIVGVI   450
 451  LLYYILGVSALIGAAVIILLAPVQYFVATKLSQAQRSTLEYSNERLKQTN   500
 501  EMLRGIKLLKLYAWENIFRTRVETTRRKEMTSLRAFAIYTSISIFMNTAI   550
 551  PIAAVLITFVGHVSFFKEADFSPSVAFASLSLFHILVTPLFLLSSVVRST   600
 601  VKALVSVQKLSEFLSSAEIREEQCAPHEPTPQGPASKYQAVPLRVVNRKR   650
 651  PAREDCRGLTGPLQSLVPSADGDADNCCVQIMGGYFTWTPDGIPTLSNIT   700
 701  IRIPRGQLTMIVGQVGCGKSSLLLAALGEMQKVSGAVFWSSLPDSEIGED   750
 751  PSPERETATDLDIRKRGPVAYASQKPWLLNATVEENIIFESPFNKQRYKM   800
 801  VIEACSLQPDIDILPHGDQTQIGERGINLSGGQRQRISVARALYQHANVV   850
 851  FLDDPFSALDIHLSDHLMQAGILELLRDDKRTVVLVTHKLQYLPHADWII   900
 901  AMKDGTIQREGTLKDFQRSECQLFEHWKTLMNRQDQELEKETVTERKATE   950
 951  PPQGLSRAMSSRDGLLQDEEEEEEEAAESEEDDNLSSMLHQRAEIPWRAC  1000
1001  AKYLSSAGILLLSLLVFSQLLKHMVLVAIDYWLAKWTDSALTLTPAARNC  1050
1051  SLSQECTLDQTVYAMVFTVLCSLGIVLCLVTSVTVEWTGLKVAKRLHRSL  1100
1101  LNRIILAPMRFFETTPLGSILNRFSSDCNTIDQHIPSTLECLSRSTLLCV  1150
1151  SALAVISYVTPVFLVALLPLAIVCYFIQKYFRVASRDLQQLDDTTQLPLL  1200
1201  SHFAETVEGLTTIRAFRYEARFQQKLLEYTDSNNIASLFLTAANRWLEVR  1250
1251  MEYIGACVVLIAAVTSISNSLHRELSAGLVGLGLTYALMVSNYLNWMVRN  1300
1301  LADMELQLGAVKRIHGLLKTEAESYEGLLAPSLIPKNWPDQGKIQIQNLS  1350
1351  VRYDSSLKPVLKHVNALIAPGQKIGICGRTGSGKSSFSLAFFRMVDTFEG  1400
1401  HIIIDGIDIAKLPLHTLRSRLSIILQDPVLFSGTIRFNLDPERKCSDSTL  1450
1451  WEALEIAQLKLVVKALPGGLDAIITEGGENFSQGQRQLFCLARAFVRKTS  1500
1501  IFIMDEATASIDMATENILQKVVMTAFADRTVVTIAHRVHTILSADLVIV  1550
1551  LKRGAILEFDKPEKLLSRKDSVFASFVRADK                     1581

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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