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

NucPred

Fetching Q01550 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MEGYLASVSLGEESTQMWSLNKRLEAYLSRVKALEEENELLRKEIHSLRS    50
51 SKSERCWKKKHHEEMMKLRDALDDGHREMVQAEMVRDSIYEEIEFVKQRC 100
101 LEEKQAREDAKKELSESKKLLEEETRAQIWLKERLGQLEAELEDILRDHE 150
151 EEKALMEEEIASFSQRLENFRVAPVAFKPVEVDDYARKLSEIWQGAVEEY 200
201 KSEVSVLEAGLSESKENLRKVLEENKQNRLLLQSLDKELVSLKMRKEALE 250
251 DLLSKQWQEQKEEEEKLQRKAEALEQEKQDLRGQIAEVLEDRQQLMHLKM 300
301 SLSLEVATYRSLLEAESTRIYTDYRGSYTFNDSMLEHNNVRRRQSEDTRK 350
351 TVSKDHRQSYSKKQIGDKNELQRPSLNNFSTVKSSAVPVRTSPVTKEFQK 400
401 VSSVLQSQGLKYTKAPQVKEVQTVSTVKSNLETHTFSGDAFRRAQVETRK 450
451 TDEQVIKKDALGLNDLNKNTGFKEEKDIQKPGFMDHVVSKSVSSTEHKVP 500
501 EIDPLESALKSLEEDLSSVSSTFNAGQSSNLEAIKDVLGEPICLENLQNE 550
551 IAFEKESPGTNAAADPIEEVISESVSYQTVHFEKQELSNLLEIENTHENH 600
601 VQDATQAFNSCEQDGHDRASTLENNEPDVQQYIRTLESNEIKESKIPSDN 650
651 TEEAEIISKSRKVFLENEYIPVSKDDLTEFTSHLENDSESSQSFDSKLFE 700
701 NKSTEDQLITNLKSNTQENIFQSNQEHLENLEFDSVVPDTVKFMYPQENN 750
751 LLEEENVYGDGELVQMATDENIINQSSDQLLLSDHSHHEETKTSESIAVE 800
801 HNRMESEHAEVDKSSEIPVEISENVSVEEIIHEISDVEEDTKQAFEDERV 850
851 GEQINQNNQESTVDLDGSVYSQEENSQLEEDEVSISEQIEKDFEINEQEC 900
901 LKSDQIREAFDTEEVDHQVVDFMQEQSFEREVGQLNNIKQEVDYLQNYDE 950
951 DSFQNNDEPQELESCDLQEQKIKLEEENQLSENEGNQNFGGNDIEEFSQQ 1000
1001 GYDTDEICQETIGNQVSAQLLCESDINQDKLSMEDEEEQNNPETEDNIGL 1050
1051 EQESDQENTRSNEGTKFSQEECDVVFKPEDMSDKSEYSGQQEDLDKQVTD 1100
1101 FSLNEQANNDLLEKEEVILHHADDQRSVNDEITIDEKLSERIIDNELATV 1150
1151 DVNESLAANKEQVDLFTDEYAVDDNVGMQDDDSGQYQTKEDLFVDGNNII 1200
1201 EKIEIQQTSLLNQEICERVDNVDEDISGEAKNESVEMNDVVDLVPEAKVT 1250
1251 GDEQISPLQDEKLNLETMEDTKDNDGQLCLEKENETEYIEVTDSPQFATD 1300
1301 LSHDAGRELTVDQNSANLQFCENPTKTLIAHHIEYETVADSDLESTEEQV 1350
1351 QETERIPFKPEDSKMENENSESEESVDSQEISLNSHKSEEFEISKDYQLE 1400
1401 QTLPDVTPLPNLEDEFEDLTEQPDVHEEHQNNDDSGASTFITSVDEDKER 1450
1451 EVRESVSKDEESNEEEFGDVLSVDKTSQVEVTTLSGLAQEPSYLGDNEES 1500
1501 EDSMENAEILNENPSNDIVDFMVSQMTETKIIIAEQVTEQTEVTLQFDDA 1550
1551 PNKLTENLNAREKETYDYESNEENIEFTNENQSASPANDIVDENQSEDSV 1600
1601 ISDNEGTTSSYEDLPNATSISHVVALEESNISTTEQSSTDTKRMTYEGYE 1650
1651 ITSLQNVEDNAQETEKEFPSGVPLGQEDSRSEDEELDDEGSEFSFGVNDE 1700
1701 KANGEHKDVGEDDETEDMLNGHSQTGYSKIVLTSKKALRWKRMF 1744

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.