 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q750S2 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MSTFPGEDTRIPKRISEALSHQPLNHLVPKRELSRLLSKPVQISVQLESE 50
51 DAFEEVPEELWQYPHPIDLDPLRLEESQPLRFRRPRGARLDYREDSSEIA 100
101 DLPGMGQLARACLSGTQLVDSAAIVESIESNAKKRKQTLAIGDVEMVSPD 150
151 KKTKVMASVSPVSLNRVALGSQHLKTLERLMQYIGADESSAEFGDFEYWI 200
201 TLEDRATHILSEQCIDKLHIVFRNILSIPAVWTELDVSLLQRIMDVCVST 250
251 ITICLEKIELKEYSHDYTLIAFGSSMVVFFIFLLDQNDRRLQLEQYMMVP 300
301 LQFLTFTADNLEEEFDRGGNGVERSLAMLHSTLDVFYMYISNKPKLDDGL 350
351 VVKLVYMFTELIMSTWSHNVSSVSLQNHIGNVKTIGMKSIEVLFEKLPEQ 400
401 RLFIIDELLSHLDNLPNTRSQKRMKNIGKNLHITHFSYIMLSILQVWNNY 450
451 DYCSNLVSPDTEQLHDLIAHHAATQSDLEFAADHIIDTILKKCFSNISKY 500
501 RFVFDQFVTDMTTVVTLPDWPVSDLILARLLKKLLSIFNPQSQKHINIES 550
551 VALQGIGLIGSTILDIRLSSNSNPTANLIHLFNYPEDIDGLFKAYRTCLA 600
601 YCTNSVQHHTPYKFLWCKQLDVLTKLKEMDKESQGWGSKLQQKFLSLIES 650
651 IHLPLEQAANLGAVEILPTYCSTLLTSELINMYEPYLKLVLSLLERHKVK 700
701 LRSGAIRCLALLISKDKNMLYTPIVKETIENRLTDSSPLVKDAILELIEL 750
751 GSSYIDFYQHININYNDDSMLVRKHVLRMNQIIYDDTEDIIIKAYVASRI 800
801 LRRIEDEEDVIIETARSELLKRWILSIQCPNAKPELQIKNCRVSIRVIAQ 850
851 LLVGGDKICDLFEHFLIFYVLNKNAHTEDQNKLISSSLCLLTDQVIEMVI 900
901 ENEAADVDNQREEEGRNIMKFLSVLSSCQDSFITKDHITALYPYLHSDTK 950
951 SDFQLHILKVYRNTFEQLSHFKPKFLYDLETTILSRLPRMNVRELDEAIP 1000
1001 LSWSLSRHRKDDTRICKACASCLGQLSPYIANATTDPSAVRPDGKLQRLL 1050
1051 YLATGFARFCSFENTEGKFPNLKTRENIFEYVTKCLLMFTKENIHHVIRR 1100
1101 IATKNLVKIASRYPKLFNSRHVLTVLDTQFEKGILDIQLVVLESLYDFFL 1150
1151 AEERRSLIQVGVDGTISSNNELRKVVANHTKSDSINDGICSALVSRYLDK 1200
1201 ILKICLIADLNNAMVAIRFLKQILTYGYTNPSLCVPTVIALTASPNSYMR 1250
1251 DLSSEMFSELLQGYESMAFNCLNQGIRLGTEYAVKIRPKQFHEDSMFLRR 1300
1301 LQQLMSTNKRNRSKFLKVVKKTVFSNYLSTSVNYEESCYHIIYLLHNLSK 1350
1351 ISYDNMLELYEMLRSVISVSEYFSDRISERLDGFQSNQNTAAEVSAIIVT 1400
1401 RLSIEEFKRFMFEQHHLSEAKLTLLDATDDENLRNKSVAALDDQVGSLHM 1450
1451 ENIFLGYENPINNKDYCWKYISTLHRDEI 1479
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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