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

NucPred

Fetching Q9FGR0 from www.uniprot.org...

The NucPred score for your sequence is 0.36 (see score help below)

   1  MSFAAYKMMHWPTGVENCASGYITHSLSDSTLQIPIVSVHDDIEAEWPNP    50
  51  KRGIGPLPNVVITAANILEVYIVRAQEEGNTQELRNPKLAKRGGVMDGVY   100
 101  GVSLELVCHYRLHGNVESIAVLPMGGGNSSKGRDSIILTFRDAKISVLEF   150
 151  DDSIHSLRMTSMHCFEGPDWLHLKRGRESFPRGPLVKVDPQGRCGGVLVY   200
 201  GLQMIILKTSQVGSGLVGDDDAFSSGGTVSARVESSYIINLRDLEMKHVK   250
 251  DFVFLHGYIEPVIVILQEEEHTWAGRVSWKHHTCVLSALSINSTLKQHPV   300
 301  IWSAINLPHDAYKLLAVPSPIGGVLVLCANTIHYHSQSASCALALNNYAS   350
 351  SADSSQELPASNFSVELDAAHGTWISNDVALLSTKSGELLLLTLIYDGRA   400
 401  VQRLDLSKSKASVLASDITSVGNSLFFLGSRLGDSLLVQFSCRSGPAASL   450
 451  PGLRDEDEDIEGEGHQAKRLRMTSDTFQDTIGNEELSLFGSTPNNSDSAQ   500
 501  KSFSFAVRDSLVNVGPVKDFAYGLRINADANATGVSKQSNYELVCCSGHG   550
 551  KNGALCVLRQSIRPEMITEVELPGCKGIWTVYHKSSRGHNADSSKMAADE   600
 601  DEYHAYLIISLEARTMVLETADLLTEVTESVDYYVQGRTIAAGNLFGRRR   650
 651  VIQVFEHGARILDGSFMNQELSFGASNSESNSGSESSTVSSVSIADPYVL   700
 701  LRMTDDSIRLLVGDPSTCTVSISSPSVLEGSKRKISACTLYHDKGPEPWL   750
 751  RKASTDAWLSSGVGEAVDSVDGGPQDQGDIYCVVCYESGALEIFDVPSFN   800
 801  CVFSVDKFASGRRHLSDMPIHELEYELNKNSEDNTSSKEIKNTRVVELAM   850
 851  QRWSGHHTRPFLFAVLADGTILCYHAYLFDGVDSTKAENSLSSENPAALN   900
 901  SSGSSKLRNLKFLRIPLDTSTREGTSDGVASQRITMFKNISGHQGFFLSG   950
 951  SRPGWCMLFRERLRFHSQLCDGSIAAFTVLHNVNCNHGFIYVTAQGVLKI  1000
1001  CQLPSASIYDNYWPVQKIPLKATPHQVTYYAEKNLYPLIVSYPVSKPLNQ  1050
1051  VLSSLVDQEAGQQLDNHNMSSDDLQRTYTVEEFEIQILEPERSGGPWETK  1100
1101  AKIPMQTSEHALTVRVVTLLNASTGENETLLAVGTAYVQGEDVAARGRVL  1150
1151  LFSFGKNGDNSQNVVTEVYSRELKGAISAVASIQGHLLISSGPKIILHKW  1200
1201  NGTELNGVAFFDAPPLYVVSMNVVKSFILLGDVHKSIYFLSWKEQGSQLS  1250
1251  LLAKDFESLDCFATEFLIDGSTLSLAVSDEQKNIQVFYYAPKMIESWKGL  1300
1301  KLLSRAEFHVGAHVSKFLRLQMVSSGADKINRFALLFGTLDGSFGCIAPL  1350
1351  DEVTFRRLQSLQKKLVDAVPHVAGLNPLAFRQFRSSGKARRSGPDSIVDC  1400
1401  ELLCHYEMLPLEEQLELAHQIGTTRYSILKDLVDLSVGTSFL          1442

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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