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

NucPred

Fetching Q9BZF9 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MKSLKSRLRRQDVPGPASSGAAAASAHAADWNKYDDRLMKAAERGDVEKV    50
  51  TSILAKKGVNPGKLDVEGRSVFHVVTSKGNLECLNAILIHGVDITTSDTA   100
 101  GRNALHLAAKYGHALCLQKLLQYNCPTEHADLQGRTALHDAAMADCPSSI   150
 151  QLLCDHGASVNAKDVDGRTPLVLATQMSRPTICQLLIDRGADVNSRDKQN   200
 201  RTALMLGCEYGCRDAVEVLIKNGADISLLDALGHDSSYYARIGDNLDILT   250
 251  LLKTASENTNKGRELWKKGPSLQQRNLTHMQDEVNVKSHQREHQNIQDLE   300
 301  IENEDLKERLRKIQQEQRILLDKVNGLQLQLNEEVMVADDLESEREKLKS   350
 351  LLAAKEKQHEESLRTIEALKNRFKYFESDHLGSGSHFSNRKEDMLLKQGQ   400
 401  MYMADSQCTSPGIPAHMQSRSMLRPLELSLPSQTSYSENEILKKELEAMR   450
 451  TFCESAKQDRLKLQNELAHKVAECKALALECERVKEDSDEQIKQLEDALK   500
 501  DVQKRMYESEGKVKQMQTHFLALKEHLTSEAASGNHRLTEELKDQLKDLK   550
 551  VKYEGASAEVGKLRNQIKQNEMIVEEFKRDEGKLIEENKRLQKELSMCEM   600
 601  EREKKGRKVTEMEGQAKELSAKLALSIPAEKFENMKSSLSNEVNEKAKKL   650
 651  VEMEREHEKSLSEIRQLKRELENVKAKLAQHVKPEEHEQVKSRLEQKSGE   700
 701  LGKKITELTLKNQTLQKEIEKVYLDNKLLKEQAHNLTIEMKNHYVPLKVS   750
 751  EDMKKSHDAIIDDLNRKLLDVTQKYTEKKLEMEKLLLENDSLSKDVSRLE   800
 801  TVFVPPEKHEKEIIALKSNIVELKKQLSELKKKCGEDQEKIHALTSENTN   850
 851  LKKMMSNQYVPVKTHEEVKMTLNDTLAKTNRELLDVKKKFEDINQEFVKI   900
 901  KDKNEILKRNLENTQNQIKAEYISLAEHEAKMSSLSQSMRKVQDSNAEIL   950
 951  ANYRKGQEEIVTLHAEIKAQKKELDTIQECIKVKYAPIVSFEECERKFKA  1000
1001  TEKELKDQLSEQTQKYSVSEEEVKKNKQENDKLKKEIFTLQKDLRDKTVL  1050
1051  IEKSHEMERALSRKTDELNKQLKDLSQKYTEVKNVKEKLVEENAKQTSEI  1100
1101  LAVQNLLQKQHVPLEQVEALKKSLNGTIENLKEELKSMQRCYEKEQQTVT  1150
1151  KLHQLLENQKNSSVPLAEHLQIKEAFEKEVGIIKASLREKEEESQNKMEE  1200
1201  VSKLQSEVQNTKQALKKLETREVVDLSKYKATKSDLETQISSLNEKLANL  1250
1251  NRKYEEVCEEVLHAKKKEISAKDEKELLHFSIEQEIKDQKERCDKSLTTI  1300
1301  TELQRRIQESAKQIEAKDNKITELLNDVERLKQALNGLSQLTYTSGNPTK  1350
1351  RQSQLIDTLQHQVKSLEQQLADADRQHQEVIAIYRTHLLSAAQGHMDEDV  1400
1401  QEALLQIIQMRQGLVC                                    1416

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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