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

NucPred

Fetching Q9VJE5 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MSDDTSASGGTSAPFPSPVTADPEPGATASKLPGPIRSNIPTPATSGTGI    50
  51  PQPSKMKAPSSFGSTGSVSKIGRPCCNHTTPKSGPPPREATSMSRESDDN   100
 101  LSSINSAYTDNSSAVLTANTEQFIIGQRVWLGGTRPGQIAFIGDTHFAAG   150
 151  EWAGVVLDEPNGKNDGCVSGKRYFQCEPKRGIFSRLTRLTTYPLAGAQTP   200
 201  TSPLAKSSPDRSRTVSPTASIRSSMLRSPGIGGKNGMAVGDRVIVSSGFG   250
 251  SRPGILRYLGETQFAPGNWCGVELDEPSGKNDGTVDDIRYFECKPKYGVF   300
 301  VPIAKVSLSPSSKKTRLSRTGSRESLTSIGTMNSIATTATSRMRMNAQQR   350
 351  KSSTPVKPILATPKSQFSMQDLLREKQQHVEKLMVERDLDREDAQNQALQ   400
 401  LQKNINELKARIVELESALDNERKKTEELQCSIDEAQFCGDELNAQSQVY   450
 451  KEKIHDLESKITKLVSATPSLQSILPPDLPSDDGALQEEIAKLQEKMTIQ   500
 501  QKEVESRIAEQLEEEQRLRENVKYLNEQIATLQSELVSKDEALEKFSLSE   550
 551  CGIENLRRELELLKEENEKQAQEAQAEFTRKLAEKSVEVLRLSSELQNLK   600
 601  ATSDSLESERVNKTDECEILQTEVRMRDEQIRELNQQLDEVTTQLNVQKA   650
 651  DSSALDDMLRLQKEGTEEKSTLLEKTEKELVQSKEQAAKTLNDKEQLEKQ   700
 701  ISDLKQLAEQEKLVREMTENAINQIQLEKESIEQQLALKQNELEDFQKKQ   750
 751  SESEVHLQEIKAQNTQKDFELVESGESLKKLQQQLEQKTLGHEKLQAALE   800
 801  ELKKEKETIIKEKEQELQQLQSKSAESESALKVVQVQLEQLQQQAAASGE   850
 851  EGSKTVAKLHDEISQLKSQAEETQSELKSTQSNLEAKSKQLEAANGSLEE   900
 901  EAKKSGHLLEQITKLKSEVGETQAALSSCHTDVESKTKQLEAANAALEKV   950
 951  NKEYAESRAEASDLQDKVKEITDTLHAELQAERSSSSALHTKLSKFSDEI  1000
1001  ATGHKELTSKADAWSQEMLQKEKELQELRQQLQDSQDSQTKLKAEGERKE  1050
1051  KSFEESIKNLQEEVTKAKTENLELSTGTQTTIKDLQERLEITNAELQHKE  1100
1101  KMASEDAQKIADLKTLVEAIQVANANISATNAELSTVLEVLQAEKSETNH  1150
1151  IFELFEMEADMNSERLIEKVTGIKEELKETHLQLDERQKKFEELEEKLKQ  1200
1201  AQQSEQKLQQESQTSKEKLTEIQQSLQELQDSVKQKEELVQNLEEKVRES  1250
1251  SSIIEAQNTKLNESNVQLENKTSCLKETQDQLLESQKKEKQLQEEAAKLS  1300
1301  GELQQVQEANGDIKDSLVKVEELVKVLEEKLQAATSQLDAQQATNKELQE  1350
1351  LLVKSQENEGNLQGESLAVTEKLQQLEQANGELKEALCQKENGLKELQGK  1400
1401  LDESNTVLESQKKSHNEIQDKLEQAQQKERTLQEETSKLAEQLSQLKQAN  1450
1451  EELQKSLQQKQLLLEKGNEFDTQLAEYQKVIDEMDDAASVKSALLEQLQN  1500
1501  RVAELETALRQANDAQKTAYLETKELRRQLESLELEKSREVLSLKAQMNG  1550
1551  ASSRSGKGDEVESLDIETSLAKINFLNSIIADMQQKNDALKAKVQTLETL  1600
1601  PMDFTKPHAFDALTKRKPAPRLFCDICDEFDQHDTEDCPIQGSEDQDYST  1650
1651  PSSESNNNEKERKLPAPRKYCDSCEVFGHDTSECADDETY            1690

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.