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

NucPred

Fetching O14299 from www.uniprot.org...

The NucPred score for your sequence is 0.81 (see score help below)

   1  MGLEHTFYPAEDRFEPLLEHSEPVNFVPKENAKSYVRQGFASPHQSLMDN    50
  51  LVDSTESTKRSENFVSHIPLTPSHSGQSEKLMSTRTSHSPYISPTMSYTN   100
 101  HSPANLTRNSSFNHQHYSTTLRSPPSMRGRGIDVNSSHYPHISRPRTSSD   150
 151  SQKMYTRAPVDYYYIQENPYFNNIDQDSISDKSLPSTNQSLHHSEEDTES   200
 201  DNDFSESIHPEFDIDVFYKVSNILYDESDLQDPEKRERLEWHSMLSSVLK   250
 251  GDVMQTEKRRLRLTEPDGHSGTYISEVWLGLQAWLHGRLNADQAEVIRKS   300
 301  REGVEPVLREVIDFQIQDEETTKPPLEQVTEILEKVEQCKQFYISSREME   350
 351  ENVPLSASKEFNYKLNALISWSNVMESIQVETLVLQKWVGNDEFDLTMRT   400
 401  PQFNYDGVENTSSFVERIFRQSGLQRTFEQRTLTTLNRIIHQAKQTISEN   450
 451  AQAFEEMKLPTYEDKLLPLVRFPIKLLEEALRLRLAYAKKIKGPNFLIVD   500
 501  SMLDDFKIALSVAVRIKREYIKIASPSPGWSLPTNVDEDYDNVLLDSLKF   550
 551  YFKLLTLKLSSGNKNLYFKEIDFLENEWAFLNEHIYWINGGDIHMAGQFS   600
 601  YLSNSLLLNVHRYVESHLNGPTERTAASLTNWYSTLLKNTQIRFRKILRF   650
 651  SETLNSRFENASDFVISEGHLPDLVNRLSTTGHFLAYTANLERDGVFVIA   700
 701  DHTLSENPEALKALLFSKDISNLETIQQNCSYVLILCPVHPIVWKGRIEK   750
 751  VDVPDFSVDLKTNRVRIIASNKREHLQAAKSVFQSISGDLVTLAVECRSS   800
 801  ITRVYKEFIRLSKLCMRISSTVVDCVSAVREACSGVNCHDLIYHVFSFAA   850
 851  EFGQRILRFLSFDSYWQTKLKRKITSLAVEWISFICDECDLMDRKTFRWG   900
 901  VGALEFLMLMIRGNNILLIDDAMFLKIREKVGKSMAFLLTHFDVLGAKSK   950
 951  VAAKLQRESTEVSSSPRLTSFGDVEEEALSIQLLQKETMLRIDELEIERN  1000
1001  NTLLERLAIGHVLDDSVFRNRDFIKLASSFSNITIRWQQGHFVRSGMFGD  1050
1051  VYTGVNMETGDLLAVKEIKLQDSRTFRSTVDQIHNEMTVLERLNHPNVVT  1100
1101  YYGVEVHREKVYIFMEFCQGGSLADLLAHGRIEDENVLKVYVVQLLEGLA  1150
1151  YIHSQHILHRDIKPANILLDHRGMIKYSDFGSALYVSPPTDPEVRYEDIQ  1200
1201  PELQHLAGTPMYMAPEIILGTKKGDFGAMDIWSLGCVILEMMTGSTPWSE  1250
1251  MDNEWAIMYHVAAMHTPSIPQNEKISSLARDFIEQCFERDPEQRPRAVDL  1300
1301  LTHPWITDFRKKTIITMPPATITKKTSLSHTITEEKTAQLLAGRHDDSKA  1350
1351  ETDSLAASYKEESALPVASNVGLRQPNELRIDSINLPPAIVTPDTINYSV  1400
1401  D                                                   1401

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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