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

NucPred

Fetching O94823 from www.uniprot.org...

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

   1  MALSVDSSWHRWQWRVRDGFPHCPSETTPLLSPEKGRQSYNLTQQRVVFP    50
  51  NNSIFHQDWEEVSRRYPGNRTCTTKYTLFTFLPRNLFEQFHRWANLYFLF   100
 101  LVILNWMPSMEVFHREITMLPLAIVLFVIMIKDGMEDFKRHRFDKAINCS   150
 151  NIRIYERKEQTYVQKCWKDVRVGDFIQMKCNEIVPADILLLFSSDPNGIC   200
 201  HLETASLDGETNLKQRCVVKGFSQQEVQFEPELFHNTIVCEKPNNHLNKF   250
 251  KGYMEHPDQTRTGFGCESLLLRGCTIRNTEMAVGIVIYAGHETKAMLNNS   300
 301  GPRYKRSKIERRMNIDIFFCIGILILMCLIGAVGHSIWNGTFEEHPPFDV   350
 351  PDANGSFLPSALGGFYMFLTMIILLQVLIPISLYVSIELVKLGQVFFLSN   400
 401  DLDLYDEETDLSIQCRALNIAEDLGQIQYIFSDKTGTLTENKMVFRRCTI   450
 451  MGSEYSHQENAKRLETPKELDSDGEEWTQYQCLSFSARWAQDPATMRSQK   500
 501  GAQPLRRSQSARVPIQGHYRQRSMGHRESSQPPVAFSSSIEKDVTPDKNL   550
 551  LTKVRDAALWLETLSDSRPAKASLSTTSSIADFFLALTICNSVMVSTTTE   600
 601  PRQRVTIKPSSKALGTSLEKIQQLFQKLKLLSLSQSFSSTAPSDTDLGES   650
 651  LGANVATTDSDERDDASVCSGGDSTDDGGYRSSMWDQGDILESGSGTSLE   700
 701  EALEAPATDLARPEFCYEAESPDEAALVHAAHAYSFTLVSRTPEQVTVRL   750
 751  PQGTCLTFSLLCTLGFDSVRKRMSVVVRHPLTGEIVVYTKGADSVIMDLL   800
 801  EDPACVPDINMEKKLRKIRARTQKHLDLYARDGLRTLCIAKKVVSEEDFR   850
 851  RWASFRREAEASLDNRDELLMETAQHLENQLTLLGATGIEDRLQEGVPDT   900
 901  IATLREAGIQLWVLTGDKQETAVNIAHSCRLLNQTDTVYTINTENQETCE   950
 951  SILNCALEELKQFRELQKPDRKLFGFRLPSKTPSITSEAVVPEAGLVIDG  1000
1001  KTLNAIFQGKLEKKFLELTQYCRSVLCCRSTPLQKSMIVKLVRDKLRVMT  1050
1051  LSIGDGANDVSMIQAADIGIGISGQEGMQAVMSSDFAITRFKHLKKLLLV  1100
1101  HGHWCYSRLARMVVYYLYKNVCYVNLLFWYQFFCGFSSSTMIDYWQMIFF  1150
1151  NLFFTSLPPLVFGVLDKDISAETLLALPELYKSGQNSECYNLSTFWISMV  1200
1201  DAFYQSLICFFIPYLAYKGSDIDVFTFGTPINTISLTTILLHQAMEMKTW  1250
1251  TIFHGVVLLGSFLMYFLVSLLYNATCVICNSPTNPYWVMEGQLSNPTFYL  1300
1301  VCFLTPVVALLPRYFFLSLQGTCGKSLISKAQKIDKLPPDKRNLEIQSWR  1350
1351  SRQRPAPVPEVARPTHHPVSSITGQDFSASTPKSSNPPKRKHVEESVLHE  1400
1401  QRCGTECMRDDSCSGDSSAQLSSGEHLLGPNRIMAYSRGQTDMCRCSKRS  1450
1451  SHRRSQSSLTI                                         1461

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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