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

NucPred

Fetching Q9YHY6 from www.uniprot.org...

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

   1  MTFHFHIPLAFRDLLKSGGIGQYVVQEVLPVRHVDAQFAAFQTSFRTEAP    50
  51  LCILQHFDTLYSILHHFRSLDIAIKEDVLEVMVKVASRHANELPAILEDL   100
 101  NLSVPQRAAHLNALKMNCFILTQLIEAFEAETYKASLGSVEPSGKGKKAK   150
 151  SKPEGFSWESERESILQALTHLLQLDIRRLWSMSVVEEEFVSMMTSCCYK   200
 201  MMENPNIVMAKNKSTREALGHLLGVTVKRYNHMLSASVKVIQLLQHFEHL   250
 251  ASVLVHTVSLWATEYGMKPVIGEIMREIGQKCSQDLSRESSGFKAFATFL   300
 301  TELAERIPAIMMPSISVLLDYLDGENYMMRNSVLTVMGEMVVRVLSGDQL   350
 351  EEAEKSSRDQFLDTLQEHLHDVNTYVRSCVIQIYNRIVQEKALPLSRFQS   400
 401  VVTLVVGRLFDKSVNVCKNAIQLLASFLANNPFTCKLSSVDLKVPLEKET   450
 451  KKLKEMREKYQGPKPVVVISPEEEWEAMLPEVLEAFKILQQESKEEEDIE   500
 501  TEEIESSQHLREQILILLRKTSYKNSIRLTQKGIERFQEDPLFSEGDSEA   550
 551  KSELGILEKIFTEKKADLEQPTTKDQDDAQVNPTSEELPSQEVQNSDMDK   600
 601  QEMLVQYLSDAHHFALKIEEAIDVISKMMYETAVSVVQEVIEFFVTVSQF   650
 651  GVSQALLGVRRMLPLVWSKEPGVREAVLSAYRRLYLSSNGESERVKAQAL   700
 701  VRSLSLLMVDSSAGILQCLEEIVSEFVQKGDIHPSVIQLLWEKFTQKSPC   750
 751  SEFERRAAVMLLGMMTRGQPEIVMSNLDTLVSVGLGEQVQKDYQLAREVC   800
 801  NCILKITDSQKQTLGKSTEPFRLPKDHSLFVCLTEAVAGGIGLSGLHWLP   850
 851  FKETAVRLVYELGEEPEEICSEILLRCSQNVLDGHQTQDEVPNVPAFLLT   900
 901  HLLSLAGDVALQQVVHLERAVSAELRRRRVLKEEQEAEKVGKQRKSKANE   950
 951  STMEEELGLVGASADDIEAELIRKICDTELLGGQQYLSAFLPLILRICNN  1000
1001  PGRYSDPDLCTVATLALAKYMMISSDFCDTHLRLLFTLLEKSPLPSVRSN  1050
1051  IMIALGDLSIRFPNLIEPWTPNLYARLRDPSREVRKTAGMVMTHLILKDM  1100
1101  VKVKGQVSEMAVLLIESDQEISALARNFFNELSNKGNAVYNLLPDIISRL  1150
1151  SDPDCGVEEEAFRTIMKQLLSYITKDKQTESLVEKMCHRFRTARTERQWR  1200
1201  DLAHCLSLLPFSEKGLRKMQDCFDCYGDKLSDEAVYNSFLTTVAKMRRGA  1250
1251  KPELKALIDEFEQKLSRCHNKGLENMDVPEEPSAESDAQPPKAKRPPLAS  1300
1301  VNVKKGKSEDDFQTPKPPASRKSRRKVAVNFSSDEESDLEAELSEAETPK  1350
1351  NPTPIRRTARSRAK                                      1364

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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