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

NucPred

Fetching Q90941 from www.uniprot.org...

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

   1  MGSKRRRATSPSSSVSGGDFDDGHHSTNIPGPSRKRRRLSNLPTVDPIAV    50
  51  CHELYNTIRDYKDEQGRLLCELFIRAPKRRNQPDYYEVVSQPIDLMKIQQ   100
 101  KLKMEEYDDVNVLTADFQLLFNNAKAYYKPDSPEYKAACKLWELYLRTKN   150
 151  EFVQKGDAEEEDEDEEGHDSQELSSPGYLKEILEQLLEAVAVATNPSGRL   200
 201  ISELFQKLPSKVQYPDYYAIIKEPIDLKTIAQRIQNGTYKSIHAMAKDID   250
 251  LLAKNAKTYNEPGSQVFKDANAIKKIFNMKKAEIEHSELAKSSLRLRTPS   300
 301  NLTASKLTGPSSQGKGSVGDERNSSNKYFRNKRSAQGDRLSAITMALQYG   350
 351  SESDEDAALAAAARYEGESEAESITSFMDTSNPLYQLYDTVRSCRNNQGQ   400
 401  LISEPFFQLPSKKKYPDYYQQIKTPISLQQIRAKLKNHEYETLDQLEADL   450
 451  NLMFENAKRYNVPNSAIYKRVLKMQQVMQAKKKELARRDDIEDGDSMISS   500
 501  ATSDTGSSKRKSKKNMRKQRMKILYNAVLEARESGTGRRLCDLFMVKPSK   550
 551  KDYPDYYKIILEPMDLKMIEHNIRNDKYVGEEAMIDDMKLMFRNARHYNE   600
 601  EGSQVYNDAHMLEKILKEKRKELGPLPEDDDVASPKLKLSRKSGISPKKS   650
 651  KYMTPMQQKLNEVYEAVKNYTDKRGRRLSAIFLRLPSRSELPDYYITIKK   700
 701  PVDMEKIRSHMMANKYQDIDSMVEDFVMMFNNACTYNEPESLIYKDALVL   750
 751  HKVLLETRREIEGDEDSHVPNVTLLIQELIHNLFVSVMSHQDDEGRCYSD   800
 801  SLAEIPAVDPNFPNKPPLTFDIIRKNVENNRYRRLDLFQENMFEVLERAR   850
 851  RMNRTDSEIYEDAVELQQFFIKIRDELCKNGEILLSPALSYTTKHLHNDV   900
 901  EKEKKEKLPKEIEEDKLKREEEKREAEKSEDSSGSAGLSSLHRTYSQDCS   950
 951  FKNSMYHVGDYVYVEPAEANLQPHIVCIERLWEDSAGEKWLYGCWFYRPN  1000
1001  ETFHLATRKFLEKEVFKSDYYNKVPVSKILGKCVVMFVKEYFKLCPENFR  1050
1051  DEDVYVCESRYSAKTKSFKKIKLWTMPVSSVRFVPRDVPLPVVRVASVFA  1100
1101  NTDKAEEEKHSDTLDDSKVGESILHLEKDKEDVPVEMSNGEPGCHYFEQL  1150
1151  CYNDMWLKVGDCVFIKSHGLVRPRVGRIEKMWVRDGAAYFFGPIFIHPEE  1200
1201  TEHEPTKMFYKKEVFLSNLEETCPMSCILGKCAVLSFKDFLCCRPTEISE  1250
1251  NDVFLCESRYNESDKQMKKFKGLKRFSLSAKVVDDEIYYFRKPIVPQKEP  1300
1301  SPLLEKKIQQLEAKFAELGGGDEDMEEMGEEEGDITETPSMPQLQTPLTS  1350
1351  ELDIMPYTPPQSTPKSVKGSTKKEGSKRKINMSGYILFSSEMRPVIKAQH  1400
1401  PDYSFGELSRLVGTEWRNLEATKKAEYEGMISGYPPVLPPLQGPVDGIVS  1450
1451  MGSMQPLHPGVPPPHQLPPGMPGIPGIPPPGVIGQNVSPMVGTPAPGAGP  1500
1501  FGQQIGILGPPGQQAPPPYPGQSPATQPVMQQPSTPMFVSPPPKTQRLLH  1550
1551  SEAYLKYIEGLSAESNSISKWDQTLAARRRDVHLSKEQESRLPSHWLKSK  1600
1601  GAHTTMADALWRLRDLMLRDTLNIRQAYNIENV                   1633

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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