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

NucPred

Fetching Q5B7Q7 from www.uniprot.org...

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

   1  MSARDFVEGEAMLDEEENEEELVDDYGDGEERLETGGNHYDSSEEDEDED    50
  51  DDEDAVRAVREGFIVDEDEEEEERAERRRERRKRRREEREREDEHLDEED   100
 101  LELIGELNPGLQYAAAADSKFKRLKRGHKDRDSRQPSQAINDFFNSDEED   150
 151  EPAPDYGRHRRHPGDEMDDFIEEDVFSDDELQREREDLEVARPRKTIGFG   200
 201  ATDTTGLDENALEDMRAAFGDGNEYDFALAMEEEEEQQEEDVEKHLDLKD   250
 251  VFEPSQLAEKMLTEEDNQIRLIDEPERHQIARKPYRNVVLSEDQFREEAA   300
 301  WIANLMLLKKRLEPELREPFQRSVAKVLEFLVTDDWEVPFIFQHRKDYMI   350
 351  HTVKVPVNGASADDSSSQYTIKAEKLLNMTDLWDIFDYDLKFKALVEKRN   400
 401  TIQKTYDNIRSVFSVEDPIVEEMLPIATTMEELQDIQDYLHFQYASQIRD   450
 451  LTLTNGDTNGEVQRRKALTRNFFERVRNSKAYGLVRAFGITADAFAQNAL   500
 501  KEGRRQYTEDASERPEDMADGLVDNDFNNSSQVLKAAKGMFAEEIVMSPK   550
 551  MRKVIRQAYYMNGAVDCFRTEKGLRRIDEQHPYYEFKYLRDQQLSDIARS   600
 601  PELFLRMLKAEEEGLIEVKVRFENFENFRKRLYPNIESDNYSELADSWNR   650
 651  LRREAVDLALGKLERVINRSVKENIRQECENHVAKECREAFSQRLDQAPY   700
 701  KPKGMILGTVPRVLALSTGTGIIGRAPIHWAYVEEDGRVLENGKFTDLSL   750
 751  GDKDRGIADGKDLEALVELVNRRRPDVIGVSGMSPETRRLYKLLTEIVDA   800
 801  KDLRGALYTDDRDEEVSDRLEVVIVNDEVARLYQNSDRAKKDHPSFAPLT   850
 851  HYCVGLAKYLQSPLKEYASLGRDIVSIQFKPGQQLVAQELLLKQLETALV   900
 901  DMVNLVGVDINEAVSDPATANLLPYVCGLGPRKAAHLLKIVNMTGGVVNS   950
 951  RFSLLGVGVQYPAMGVKVWNNSASFLYIDYESADADSDPLDNTRVHPEDY  1000
1001  DIARKMAADALELDEEDIKAETDENGPGAIVRKLFREDAQDRVNDLILEE  1050
1051  YAEQLEKNLNQRKRATLETIRAELQQPYEELRKHFVFLSTDDIFTMLTGE  1100
1101  TAQTLAEGMVVPISIKSIRDDHIEGKLDCGVDALVGESEMTDRYDIPVRA  1150
1151  IYSLHQTVPAKVMFLNRKTFTCNVSLREEQVSRPSRPAADRAHAGEWDYR  1200
1201  QEEQDREALEAKTQDGGRTMRVIKHPLFRPFNSTQAVEFLGSQSRGDVVI  1250
1251  RPSSKGPDHLAVTWKVADGIFQHIDVLELDKENEFSVGRTLKVGGRFTYS  1300
1301  DLDDLIFNHVKAMAKKVDEMMLHEKYQEGSKDSTYQWLETYTKANPRRSA  1350
1351  YAFCIDPKHAGYFFLCFKAGEHAQVHSWPVKVIPQGYELQRNPYPDMRAL  1400
1401  CNGFKLLFTNMQSGKRR                                   1417

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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