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

NucPred

Fetching P51533 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MLQAPSSSNSGLNQGNAAPDGPPNETQPYEGLDAAAQEEIKELARTLTSQ    50
  51  SSLLSQEKRITGTGDPNTLTAASSSSLSRSIFASDIKGVNPILLDVNDPD   100
 101  YDETLDPRSENFSSVRWVRNMAQICENDSDFYKPFSLGCAWKDLSASGDS   150
 151  ADITYQGTFGNMPIKYLKMSWRCISRRLFHRTHGKSEDNDSGFQILKPMD   200
 201  GCINPGELLVVLGRPGAGCTTLLKSISVNTHGFKISPDTIITYNGFSNKE   250
 251  IKNHYRGEVVYNAESDIHIPHLTVFQTLYTVARLKTPRNRIKGVDRDTFA   300
 301  KHMTEVAMATYGLSHTADTKVGNDFVRGVSGGERKRVSIAEVSICGSKFQ   350
 351  CWDNATRGLDSATALEFIKALKTQATITKSAATVAIYQCSKDAYDLFDKV   400
 401  CVLYDGYQIFFGPSKQAKKYFQRMGYVCPERQTTADYLTSITSPSERIKD   450
 451  KDMVKHGIMIPQTAYEMNQYWIQSEEYKQLQVQVNKHLDTDSSQQREQIK   500
 501  NAHIAKQSKRARPSSPYTVSFFLQVKYILIRDIWRIKNDPSIQLFTVLSH   550
 551  AAMALILGSMFYEVMLSTTTTTFYYRGAAIFFAILFNAFSSLLEIFSLYE   600
 601  TRPITEKHKTYSLYRPSADAFASTFSDVPTKLATAVTFNIPYYFLINLKR   650
 651  DAGAFFFYFLINIITVFAMSHLFRCIGSVSKTLPQAMVPASVLLLAFAMY   700
 701  TGFAIPRVQMLGWSKWISYINPLSYLFESLMINEFHGRNFPCAQYIPSGP   750
 751  NYVNATGDEVTCSALGSIPGNNYVSGDDFIQTNYGYRHKNKWRSVGIGLA   800
 801  YIIFFLFLYLFFCEYNEGAKQNGEMLVFPHSVVKKMKKKGIVSEKKKKNQ   850
 851  PTLSTSDAEKDVEMNNNSSATDSRFLRDSDAAIMGNDKTVAKEHYSSPSS   900
 901  SASQSNSFSKSDDIELSKSQAIFHWKNLCYDIPIKNGKRRILDNVDGWVK   950
 951  PGTLTALIGASGAGKTTLLDCLAERTTMGLITGDVFVDGRPRDQSFPRSI  1000
1001  GYCQQQDLHLKTATVRESLRFSAYLRQADDVSIEEKDKYVEEVIEVLEMK  1050
1051  LYADAIVGVPGEGLNVEQRKRLTIGVELAAKPKLLVFLDEPTSGLDSQTA  1100
1101  WSTCQLMKKLASRGQAILCTIHQPSALLMQEFDRLLFLQEGGQTVYFGEL  1150
1151  GKGCKTMINYFEAHGAHKCPPDANPAEWMLEIVGAAPGTHASQDYFAIWR  1200
1201  DSEEYREMQKELDWMERELPKRTEGSSNEEQKEFATSTLYQIKLVSYRLF  1250
1251  HQYWRTPFYLWSKFFSTIVSELFIGFTFFKANTSLQGLQNQMLAIFMFTV  1300
1301  VFNPILQQYLPLFVQQRELYEARERPSRTFSWKAFIVSQILVEIPWNLLA  1350
1351  GTIAFFVYYYPVGFYRNASYANQLHERGALFWLFACAFYVYISSMGVLVI  1400
1401  SCIEIAENAANLASLFFIMSLSFCGVLATPNILPRFWIFMYRVSPLTYLI  1450
1451  DALLSVGLANASVVCSSNELLKIVPPSGMTCSEYMEPYMQSTGTGYLLDG  1500
1501  SSETECHFCQFSSTNDYLATVSSSYSRRWMNYGIFSAYIVFDYCAAIFLY  1550
1551  WLVRVPKKSKKLKK                                      1564

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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