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

NucPred

Fetching Q9V7H4 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MPTQVQMRPLLRIFAEPILLILIFLFTLGAKGEKVLQETFLGLQEAPIHD    50
  51  LGDLRLVPSRLDFGTWSVGQARSQTVTLFNQHSNRTLQLNAVAGPSPAFY   100
 101  SSFLGTREVPPQGNTTFNVVFLPRQLGAIAADLLIHTSFGQAELAVQGEG   150
 151  SECPYRLKPLVGIKAPMNATLTPEIHMYNPHERPLQILEIYSSGGEFQLE   200
 201  LPSGGSEGPQNLWKIPPHTLKPVIRISFHGRTAGNHSAYIRIKVAEQELD   250
 251  IFIPVEFEILPRHSVYARNPLADFGRVATLNAPDALQFKLDVRNDESRQL   300
 301  FGSYLRQIPGLSFDANNTSIVLDASLFEGDEIINDLLVINSNQSSTSPGA   350
 351  DQPFTVLVRAEIFHGGLTFDRNATRFVTTSPEGVEGEPLERKRSLVVRNK   400
 401  FAIPLMLFNVSLTEPIDESILEVTLVGDPRILIQPDESVELLRLNLLNDQ   450
 451  VPFKSFLRIETNVTVFKLPLVSCSGRLHVSTQPIVLNFRQESLEKAAYNL   500
 501  ELDLGTVPFAEMSRDGFVILRNDNPVPVRITNWFFKHPKTVYSQSTFLGC   550
 551  RATAIGHPVSVENDTKGWHLCTEIRAGESAVFKVAIQTYEADATFGTLKV   600
 601  WTPYEVIRVRVKFEASVGHLEIDQEQLSFKNCFPGKMCTAVLSIRSSFTH   650
 651  PVHVKGISFALPVGLRFKDFNAKGTTIAPQTLTKVGRIYFDPASVCRNNC   700
 701  YIRESTNDLAIFPSVPGGGNGNSGVINNNLLYDGVELRQRTELFRQLRRQ   750
 751  LSSMSLTLHSEELPPLELDFSITIEWPKLVQFQPIPPTPAIEVGQVQRQW   800
 801  ITLTNPSQSPLLLDYFLSDPAFARRTQLSLPHEVIDVSSTSCYLTDKEVF   850
 851  SLPEAGDPILLPGGASLTIPITFSAQLPEKYCTLLHVRSNLTLYEAVWLQ   900
 901  ARAVQSQFRFGNRRPGAASPLLFEMATNQFQGCQSGNEAVVVTRSFTARN   950
 951  SGVIPIRIEGFLIGSLPCEDFGFKVMDCAGFDLGENEARKVEIAFSADFT  1000
1001  TSAVKRSLTLLTNLTYDISYKLLAQMPAESVELCASLLVRPGWESSLKNA  1050
1051  ALVVLLASFGLVLVAAVFDAKAIMVQQNAYDAARNKGPLQPTFNLRNIVK  1100
1101  LQAEEAAAKAESVQQQQKVKNGQLKELRKRTVVNSTNSKSKSKSSWSPWS  1150
1151  MDMNALSKHLQKAKPKTVVSTPVTPPAASAPAAAPVPLPEAKPVKKSSTP  1200
1201  SPQGVPISVQVRPQKKVKPTPAVVLGTTKPKQEVSTPVADQHEKSLAKSS  1250
1251  PPQQENISPKPNKPPEQRVLKEQNGSAKKMGKTPGRERERERRSKDQKLT  1300
1301  NGTGAGVGFRKPERKQRQKLNFGQTTNSTSPPESPDALKCISNPWETSSR  1350
1351  VSFRDVLRTPQMAPTDNGFDWNHATSSSDLGPIGDNRKNATPPMVTSLWE  1400
1401  PLSATASNSLFANTEVDFITPDAIYEQREREKPQWEQRSDLVMRQQLLLQ  1450
1451  QPQKLEFQLRQQEKISLLANMDPSNWATNWSPLGYSTWPNATAGIGVMRP  1500
1501  PPGLEQSARQTHNLAQEQVSAGPASGTGAALHGESLPTQYDPFTSPSSIW  1550
1551  SDTWRQSSQRNNHNHMN                                   1567

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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