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

NucPred

Fetching Q9JLM4 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MDPSDFPSPFDPLTLPEKPLAGDLPVDMEFGEDLLESQTAPSRGWAPPGP    50
  51  SPSSGALDLLDTPSGLEKDPGGVLDGATELLGLGGLLYKAPSPPEVDHGP   100
 101  EGTLAWDSGEQTLEPGPGCQTPEVMPPDPGAGASPPSPEGLLEPLAPDSP   150
 151  IILESPHIEEEIPPLATRRRGSPGQEEEHTQGQPQSPNAPPSPSVGETLG   200
 201  DGINSSQSKPGVCTPTAHPSLPGDGLTGKEIEKPPERVQKRSERVRRAEP   250
 251  PKPEVVDSTESIPVSDEDSDAMVDDPNDEDFVPFRPRRSPRMSLRSSMAQ   300
 301  RAGRSSMGTKMSCAHCRTPLQKGQTAYQRKGLPQLFCSSSCLTTYSKKPL   350
 351  GRKTCTFCKKEIWNTKDSVVVQTGPGGSFHEFCTSVCLSLYEAQQQRPIP   400
 401  QSGDPADATRCSICQKTGEVLHEVSNGSVVHRLCSDSCFSKFRANKGLKT   450
 451  NCCDQCGAYIYARPGGLGPELLFHDGQQKRFCNTTCLGAYKKKNTRVYPC   500
 501  VWCKTLCKNFEMLSHVDRNGKTSLFCSLCCTTSYKVKQAGLTGPPRPCSF   550
 551  CRRSLSDPCYYNKVDRTVYQFCSPSCWTKFQHTSPEGGIHLSCHYCHSLF   600
 601  SGKPEVLEWQDQVFQFCCRDCCEDFKRLRGVVSQCEHCRQEKLLHEKLRF   650
 651  SGVEKSFCSEGCVLLYKQDFTKKLGLCCITCTYCSQTCQRGVTEQLDGST   700
 701  WDFCSEDCKTKYLLWYCKAARCHACKRQGKLLETIHWRGQIRHFCNQQCL   750
 751  LRFYSQQNQPNLDTQSGPESLLNSQSSESKPQTPSQTKVENNHTVRTPDE   800
 801  NGNLGKTPVKRATPSVPTPPPPPPPATPRKNKAAMCKPLMQNRGVSCKAE   850
 851  MKSKGSQTEEWKPQVIVLPIPVPIFVPVPMHLYCQKVPVPFSMPIPVPVP   900
 901  MFLPTTLESTEKIVETIEELKVKIPSNPLEADILAMAEMIAEAEELDKAS   950
 951  SDLCDLVSNQSAEGLLEDCDLFGTARDDVLAMAVKMANVLDEPGQDLEAD  1000
1001  FPKNPLDINPSVDFLFDCGLVGPEDVSTEQDLPRAMRKGQKRLMLSESCS  1050
1051  RDSLSSQPSCTGLNYSYGVNAWKCWVQSKYANGETSKGDELRFGPKPMRI  1100
1101  KEDILACSAAELNYGLAQFVREITRPNGERYEPDSIYYLCLGIQQYLLEN  1150
1151  NRMVNIFTDLYYLTFVQELNKSLSTWQPTLLPNNTVFSRVEEEHLWECKQ  1200
1201  LGVYSPFVLLNTLMFFNTKFFGLQTAEEHMQLSFTNVVRQSRKCTTPRGT  1250
1251  TKVVSIRYYAPVRQRKGRDTGPGKRKREDETILEQRENRMNPLRCPVKFY  1300
1301  EFYLSKCPESLRTRNDVFYLQPERSCIAESPLWYSVIPMDRSMLESMLNR  1350
1351  ILAVREIYEELGRPGEEDLD                                1370

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.)

Go back to the NucPred Home Page.