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

NucPred

Fetching Q9BXT8 from www.uniprot.org...

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

   1  MAAEASKTGPSRSSYQRMGRKSQPWGAAEIQCTRCGRRVSRSSGHHCELQ    50
  51  CGHAFCELCLLMTEECTTIICPDCEVATAVNTRQRYYPMAGYIKEDSIME   100
 101  KLQPKTIKNCSQDFKKTADQLTTGLERSASTDKTLLNSSAVMLDTNTAEE   150
 151  IDEALNTAHHSFEQLSIAGKALEHMQKQTIEERERVIEVVEKQFDQLLAF   200
 201  FDSRKKNLCEEFARTTDDYLSNLIKAKSYIEEKKNNLNAAMNIARALQLS   250
 251  PSLRTYCDLNQIIRTLQLTSDSELAQVSSPQLRNPPRLSVNCSEIICMFN   300
 301  NMGKIEFRDSTKCYPQENEIRQNVQKKYNNKKELSCYDTYPPLEKKKVDM   350
 351  SVLTSEAPPPPLQPETNDVHLEAKNFQPQKDVATASPKTIAVLPQMGSSP   400
 401  DVIIEEIIEDNVESSAELVFVSHVIDPCHFYIRKYSQIKDAKVLEKKVNE   450
 451  FCNRSSHLDPSDILELGARIFVSSIKNGMWCRGTITELIPIEGRNTRKPC   500
 501  SPTRLFVHEVALIQIFMVDFGNSEVLIVTGVVDTHVRPEHSAKQHIALND   550
 551  LCLVLRKSEPYTEGLLKDIQPLAQPCSLKDIVPQNSNEGWEEEAKVEFLK   600
 601  MVNNKAVSMKVFREEDGVLIVDLQKPPPNKISSDMPVSLRDALVFMELAK   650
 651  FKSQSLRSHFEKNTTLHYHPPILPKEMTDVSVTVCHINSPGDFYLQLIEG   700
 701  LDILFLLKTIEEFYKSEDGENLEILCPVQDQACVAKFEDGIWYRAKVIGL   750
 751  PGHQEVEVKYVDFGNTAKITIKDVRKIKDEFLNAPEKAIKCKLAYIEPYK   800
 801  RTMQWSKEAKEKFEEKAQDKFMTCSVIKILEDNVLLVELFDSLGAPEMTT   850
 851  TSINDQLVKEGLASYEIGYILKDNSQKHIEVWDPSPEEIISNEVHNLNPV   900
 901  SAKSLPNENFQSLYNKELPVHICNVISPEKIYVQWLLTENLLNSLEEKMI   950
 951  AAYENSKWEPVKWENDMHCAVKIQDKNQWRRGQIIRMVTDTLVEVLLYDV  1000
1001  GVELVVNVDCLRKLEENLKTMGRLSLECSLVDIRPAGGSDKWTATACDCL  1050
1051  SLYLTGAVATIILQVDSEENNTTWPLPVKIFCRDEKGERVDVSKYLIKKG  1100
1101  LALRERRINNLDNSHSLSEKSLEVPLEQEDSVVTNCIKTNFDPDKKTADI  1150
1151  ISEQKVSEFQEKILEPRTTRGYKPPAIPNMNVFEATVSCVGDDGTIFVVP  1200
1201  KLSEFELIKMTNEIQSNLKCLGLLEPYFWKKGEACAVRGSDTLWYRGKVM  1250
1251  EVVGGAVRVQYLDHGFTEKIPQCHLYPILLYPDIPQFCIPCQLHNTTPVG  1300
1301  NVWQPDAIEVLQQLLSKRQVDIHIMELPKNPWEKLSIHLYFDGMSLSYFM  1350
1351  AYYKYCTSEHTEEMLKEKPRSDHDKKYEEEQWEIRFEELLSAETDTPLLP  1400
1401  PYLSSSLPSPGELYAVQVKHVVSPNEVYICLDSIETSNQSNQHSDTDDSG  1450
1451  VSGESESESLDEALQRVNKKVEALPPLTDFRTEMPCLAEYDDGLWYRAKI  1500
1501  VAIKEFNPLSILVQFVDYGSTAKLTLNRLCQIPSHLMRYPARAIKVLLAG  1550
1551  FKPPLRDLGETRIPYCPKWSMEALWAMIDCLQGKQLYAVSMAPAPEQIVT  1600
1601  LYDDEQHPVHMPLVEMGLADKDE                             1623

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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