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

NucPred

Fetching Q9P7M8 from www.uniprot.org...

The NucPred score for your sequence is 0.62 (see score help below)

   1  MGDYLLSWSWILDAFETSDENLSQNKFEELLDARIAAFQQIESPVTGTLN    50
  51  SNKTTEGEEAKLSIYDSSHSISKSQLESVKKISDITGYNEAQVAYVLLVH   100
 101  QYELNTQYFSQLDNDSVLAQEFQRRYYAEIISCWKVLAFLLQACTDADSK   150
 151  WHKMATRLIVSIFQTAQRSGENAQSTTPSIFCVRIIDYLSKMTSQAAPAS   200
 201  LTFNGEEAISQWYFFHFNLQLQLLRVIFLSTYSLVVCNSEMAISWFNCMK   250
 251  KTRYLHDQEFMHLDIDTGFSMCKEITNVAIIISINFISLEKQVLSFKDNP   300
 301  SFFMLSGNTIISLHDMITQLSNDSIGAAVSLTWGIALHLLSNSPDNIPLI   350
 351  QNSSVVSSKILQNPQNSFQALIIAALKYDPFTLIHRIISSLEDDPYIDGY   400
 401  SKIMATLFSSAVSYVKFSDSTMLCATTLFKTPQVYQLFENNDSVTRLLNF   450
 451  ARARFPFEYSQFVLLLIPTFACLTSKQLVSSELLHMTTFTQSLPSGFKAY   500
 501  EIIPEPNVTGNALIELQESLHLDSYGFFFPNAERSLPKGTRGRIVSVDTY   550
 551  PPVVMWDLNYSLWEAVGISLNYIVRNGLINSHKSFVLTVLSSSVPLFQTD   600
 601  VSGACELVHLASEGLDGELDFINVICDLLDYFLSLSVIEDADYQICVSSL   650
 651  RLLREFTRFAATDVWAYVTRSLVCVGSEKGISLEDVIFDYESINGVYDFT   700
 701  LAFFDLYEILLDNCISTSVVPDDFSIRLKTDFVKRAMRFLCEVFANYLDW   750
 751  KYARIIQQYQIGHRFASLITKLLNVTFGIEYFNPKTTVNKKTLPLRELSH   800
 801  YIVQRFLVQQDSNRYLHPLLSVMDLINLLYTDIFSTISSPRAKAAKMWLI   850
 851  SSFCAMKTLICLRGFLNLKPSELERELFSRSPDLFNCLPRLLCCIAPILQ   900
 901  LLSALILAPWPSETPSLLAYMINSTDIVGRVCIQILTNPIQSTNIEGSVW   950
 951  KFLSSIMKGQQQGLAVLLFSGKKFPLDRMKSLNHNVDVQLTSKSLISLAE  1000
1001  KRLDSFSINDILSQVPVFEFIFLSRNFWTASLGNLQQEANFWNRIVDAIK  1050
1051  LPLTVKLDGLSSVAQADLYILAAHATRITAIQLHMSKLNKSNSSKKIIID  1100
1101  PLKDSMKDLVQHAFTITAYDSNIHNALTRAFKHENGDLHISDLRNTGLFP  1150
1151  LRYGDNYFYNIKLAKNMLLNTEDTSFKISMMMSANENLSLLDAQAALLRS  1200
1201  WSIFICAFVEFVKEDATLSILELKIMKWVLKSLAEDTIDVNVVQELSAER  1250
1251  AALVFRISQQTLAIPISNEVKEHLQSILLLTWKAITTTKFSIYEDSNGEM  1300
1301  AYYRPLLHVLYNTLNRLLSEEKENLSLSVGFVSGLLQLCHRKLSQLFEKA  1350
1351  VINPTIEVYGDIVLLNSLHKCIVNSHLIRGLQSLYISYINDSFSVDNCLR  1400
1401  LFSWSHSLLVDGQPYFADAALSFLLICSSSPAGAEQIVMNGFFYSIMESP  1450
1451  LSTALSTGGLGLDGSSIQYKIWIRGILPLLFNIVKFLGNRIMNDMREFVL  1500
1501  LAFPQIQYALLNWCQPPSSISLASIDESFMIVLLFDLLQQFNPALLQEIR  1550
1551  LAELKIEMLEGIDYLISHPNFLSSLAIPASLYEQEYAIDVIGIPKELESD  1600
1601  QLTKETKTSQFAKLIRIQLDKLRALLEH                        1628

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.