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

NucPred

Fetching O88280 from www.uniprot.org...

The NucPred score for your sequence is 0.83 (see score help below)

   1  MAPGRTGAGAAVRARLALALALASILSGPPAAACPTKCTCSAASVDCHGL    50
  51  GLRAVPRGIPRNAERLDLDRNNITRITKMDFTGLKNLRVLHLEDNQVSVI   100
 101  ERGAFQDLKQLERLRLNKNKLQVLPELLFQSTPKLTRLDLSENQIQGIPR   150
 151  KAFRGVTGVKNLQLDNNHISCIEDGAFRALRDLEILTLNNNNISRILVTS   200
 201  FNHMPKIRTLRLHSNHLYCDCHLAWLSDWLRQRRTIGQFTLCMAPVHLRG   250
 251  FSVADVQKKEYVCPGPHSEAPACNANSLSCPSACSCSNNIVDCRGKGLTE   300
 301  IPANLPEGIVEIRLEQNSIKSIPAGAFIQYKKLKRIDISKNQISDIAPDA   350
 351  FQGLKSLTSLVLYGNKITEIPKGLFDGLVSLQLLLLNANKINCLRVNTFQ   400
 401  DLQNLNLLSLYDNKLQTISKGLFAPLQSIQTLHLAQNPFVCDCHLKWLAD   450
 451  YLQDNPIETSGARCSSPRRLANKRISQIKSKKFRCSGSEDYRNRFSSECF   500
 501  MDLVCPEKCRCEGTIVDCSNQKLSRIPSHLPEYTTDLRLNDNDIAVLEAT   550
 551  GIFKKLPNLRKINLSNNRIKEVREGAFDGAAGVQELMLTGNQLETMHGRM   600
 601  FRGLSGLKTLMLRSNLISCVNNDTFAGLSSVRLLSLYDNRITTISPGAFT   650
 651  TLVSLSTINLLSNPFNCNCHMAWLGRWLRKRRIVSGNPRCQKPFFLKEIP   700
 701  IQDVAIQDFTCEGNEENSCQLSPRCPEQCTCVETVVRCSNRGLHTLPKGM   750
 751  PKDVTELYLEGNHLTAVPKELSTFRQLTLIDLSNNSISMLTNHTFSNMSH   800
 801  LSTLILSYNRLRCIPVHAFNGLRSLRVLTLHGNDISSVPEGSFNDLTSLS   850
 851  HLALGINPLHCDCSLRWLSEWIKAGYKEPGIARCSSPESMADRLLLTTPT   900
 901  HRFQCKGPVDINIVAKCNACLSSPCKNNGTCSQDPVEQYRCTCPYSYKGK   950
 951  DCTVPINTCVQNPCQHGGTCHLSESHRDGFSCSCPLGFEGQRCEINPDDC  1000
1001  EDNDCENSATCVDGINNYACVCPPNYTGELCDEVIDYCVPEMNLCQHEAK  1050
1051  CISLDKGFRCECVPGYSGKLCETDNDDCVAHKCRHGAQCVDAVNGYTCIC  1100
1101  PQGFSGLFCEHPPPMVLLQTSPCDQYECQNGAQCIVVQQEPTCRCPPGFA  1150
1151  GPRCEKLITVNFVGKDSYVELASAKVRPQANISLQVATDKDNGILLYKGD  1200
1201  NDPLALELYQGHVRLVYDSLSSPPTTVYSVETVNDGQFHSVELVMLNQTL  1250
1251  NLVVDKGAPKSLGKLQKQPAVGINSPLYLGGIPTSTGLSALRQGADRPLG  1300
1301  GFHGCIHEVRINNELQDFKALPPQSLGVSPGCKSCTVCRHGLCRSVEKDS  1350
1351  VVCECHPGWTGPLCDQEAQDPCLGHSCSHGTCVATGNSYVCKCAEGYEGP  1400
1401  LCDQKNDSANACSAFKCHHGQCHISDRGEPYCLCQPGFSGNHCEQENPCL  1450
1451  GEIVREAIRRQKDYASCATASKVPIMVCRGGCGSQCCQPIRSKRRKYVFQ  1500
1501  CTDGSSFVEEVERHLECGCRECS                             1523

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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