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

NucPred

Fetching Q9Z180 from www.uniprot.org...

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

   1  MEPREMLSSCRQRGSESEFLQGSSSRSPPAPGCSGEPLKGISVGGERMEP    50
  51  EEEDELGSGRDVDCNSNADSEKWVAGDGLEEQEFSIKEANFTEGSLKLKI   100
 101  QTTKRAKKPPKNLENYICPPEIKITIKQSGDQKVSRTGKNSKATKEDERN   150
 151  HSKKKLLTAGDPTASDLKAFQTQAYERPQKHSTLQYDPGHSQGFTSDTLK   200
 201  PKHQQKSSSQSHMEWSSNSDSGPATQNCFISPEAGRDTASTSKVPALEPV   250
 251  ASFAKAQSKKGSTGGAWSQLSSSSKDLLLGSVVPSPSSHNSPATPSSSAE   300
 301  CNGLQPLGDQDGGSTKDLPEPPTLSSKKKSSKKDMISQTLPNSDLDWVKS   350
 351  AQKAFETTEGKREAYSADSAQEASPARQSISSVSNPENDSSHVRITIPIK   400
 401  TPSLDPSNHKRKKRQSIKAVVEKIVPEKALASGISMSSEVVNRILSNSEG   450
 451  SKKDPRVPKLGKMIENETPSVGLETGGNAEKIVPGGASKQRKPPMVMTSP   500
 501  TRTEHAPSGKLSEIQHPKFAAKRRCSKAKPPAMLREAVLATAEKLMVEPP   550
 551  SAYPITPSSPLYTNTDSLTVITPVKKKRGRPKKQPLLTVETIHEGTSTSP   600
 601  VSPISREFPGTKKRKRRRNLAKLAQLVPGEDKPMSEMKFHKKVGKLGVLD   650
 651  KKTIKTINKMKTLKRKNILNQILSCSSSVALKAKAPPETSPGAASIESKL   700
 701  GKQINVSKRGTIYIGKKRGRKPRTELPPPSEEPKTAIKHPRPVSSQPDVP   750
 751  AVPSSFQSPVASSPAAMHPLSTQLGGSNGNLSPASTETNFSELKTMPNLQ   800
 801  PISALPTKTQKGIHGGTWKLSPPRLMANSPSHLCEIGSLKEITLSPVSES   850
 851  HSEETIPSDSGIGTDNNSTSDQAEKSSESRRRYSFDFCSLDNPEAIPSDT   900
 901  STKNRHGHRQKHLIVDTFLAHESLKKPKHKRKRKSLQNRDDLQFLAELEE   950
 951  LITKFQVFRISHRGYTFYHENPYPSIFRINFDQYYPVPYIQYDPLLYLRR  1000
1001  TSDLKSKKKRGRPAKTNDTMTKVPFLQGFSYPIPSGSYYAPYGMPYTSMP  1050
1051  MMNLGYYGQYPAPLYLSHTLGAASPFMRPTVPPPQFHASSHVKISGATKH  1100
1101  KAKHGVHLQGTVGMGLGDIQPSLNPPKVGGATLSSSRLHKRKHKHKRKHK  1150
1151  EDRILGTHDNLSGLFAGKATGFSSHLLSERLSGSDKELPLVSEKSKHKER  1200
1201  QKHQHGEASHKVSKNNFEVDTLSTLSLSDAQHWTQAKDKGDLSSEPVESC  1250
1251  AKRYSGSGGDSTRSEGLDVFSEMNPSSDKWDSDMGGSKRRSFEGFGTYRE  1300
1301  KDIQAFKMNRKERGSYESSMSPGMPSPHLKVDQTAAHSKSEGSISAMMAR  1350
1351  KKPTAVDSVAIPSAPVLSLLAASAATSDAASSSLKKRFKRREIEAIQCEV  1400
1401  RKMCHYTKLLSTKKNLDHVNKILKAKRLQRQSKTGNNFVKKRRGRPRKQP  1450
1451  SQFDEDSRDQMPVLEKCIDLPSKRGQKPSLSPLALEPASGQDAVMATIEA  1500
1501  VIHMAREAPPLPPPPPPPLPPPPPPPPPPPPLPKTARGGKRKHRPQPPAQ  1550
1551  PAQPTPQPLPQEEEVKAKRPRKSRASESDVLP                    1582

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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