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

NucPred

Fetching Q10124 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MFNGGYGSGNSFNLQNYAPIDPMTGIPGFGPSQNAQQQQQQASAPGTSSG    50
  51  GPSQAVSGASSGASMKTEPVARQVSTAQMKRDLEQAAVYVPTPIPEGSTQ   100
 101  PQQRQQQQSQPQARQMSTQQAANLRKNAAAAGTPPKQAMQGASREQGNAH   150
 151  QPTAGQIPQSSNQPAQQTHNVPRMPQPLQQVPHPSPVRGSHPAAQQVQNA   200
 201  PQRIPQHVPMPQGVAPHQVIQQVRAPNIGASQMVQQAPSRGHTGAAPASR   250
 251  MAQQPVPLHQGVAPHQAAPQTIQQTPARGRPANAQLAQNAQQRNPQQVPM   300
 301  PQGVAPHHIPPQALGPHGAAPQMTQQAPARGPSGAAQHAQNAHRMTHQQV   350
 351  PLQAPVQGPHRGAPQMAQQPGPHGAAQHPSSGTVAPMHITSLPGNHPLNR   400
 401  THLLFNRQVVPALDIRNLIAQHRLMVDDFVRAQICYRLPENHQDYWPPGG   450
 451  HPIPMQQQQMRQGAGLPNMAMPPPPLMRHPGPHQNPIHAMQSMQVQPPLS   500
 501  PDQMNMQMFQQRALMMQQQAMQMQMQNPPPVHQQPPPQQPPQQQRQKQQR   550
 551  SQPAPARVPPQVPSQVPVTGGVAADEPPPPCSYSPVAQSSESKIEPVDVK   600
 601  PRVAPVPPQVPVTPTKPVITNNKKKRIDVVTLDEDAPRRVQVKQEIPEVS   650
 651  STSDATKSDAAPTARGAVRIKQEVESDVAPNTILISAKKFERMKAEAEDK   700
 701  EDMKKKIAALQEALFNIQEERRVEKEIAAFATTNQAVPQNQPASSVQIAQ   750
 751  VSTSESDAPGTSEAAATETMTSPKTKNNVIVETEGEQEEDEDEIPIKKSK   800
 801  KRRAKIVSNDEEEEPVRHPKRRSDEKREKRHVSYAESDDDMPVVKKKRRN   850
 851  QSPEDPEYSAASPSEDEDDDIGSFVVSDNEDDDADSFVVGDDEPIEYEEE   900
 901  DEDDMIERRSSRKRRSDSRSKKSATPTDRRRSRDTPTGSRSMRSTSPNDR   950
 951  RKSRETPPGNRSMRRTSPSDGRKSRDTPTASSSMSSSTLSYCKKSKETPM  1000
1001  SYEEIEQQKKAKRQRNCKTREENRERKRLAQLEELESSETTGVRRTLRST  1050
1051  QDNSDPLDASLATTIEEFRKTKKKDAKSSENRAKEKQKPMNKRPTSSASV  1100
1101  DSNDDGVHIPAKRMAHASSVPGPSRSKPPMIGAVKNRPNHTEMLDKRNKE  1150
1151  SEEKRRKDRDELERLRNKKHTTEEEKIKMARLQNALKVVGKAAGLKATVK  1200
1201  KELTGSPAKKQKPAPAVPKILDFSVGRTFTAIRQTAIKLVFDTFLERDSP  1250
1251  NAAREAQEFELSIAKQYTDGQKYRINIGHKVAALRKENTSGILEVNKNAV  1300
1301  SHDKILAGGPKDNCTVARGRKTHVDHRQLSIEKLHPLLLQFKLTTSELET  1350
1351  NAYPMRRDGSTKAVSIADTVYTQNKKMFLDDYDMSRNCSRCNKEFKLSPN  1400
1401  GTMIRSTGICRYHNRGVAINGKRDTFRKRYSCCNEEFNVALGCKFSDVHV  1450
1451  TDQLFKKELSTFVSTPVPVPNDQRSTRVYALDCEMVYTIAGPALARLTMV  1500
1501  DMQRNRVLDVFVKPPTDVLDPNTEFSGLTMEQINSAPDTLKTCHQKLFKY  1550
1551  VNADTILIGHSLESDLKAMRVVHKNVIDTAILFRSTRDTKVALKVLSAKL  1600
1601  LHKNIQGDNEDAIGHDSMEDALTCVDLIFYGLRNPESIAIREANTNC     1647

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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