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

NucPred

Fetching Q21874 from www.uniprot.org...

The NucPred score for your sequence is 0.61 (see score help below)

   1  MRRGCRHHLAAVVLLIATFPPLAYNQNIGGINQNIGGTPQNPTINQVSPG    50
  51  QIFSGTGNNPFYGVNLVPFGPEAGDLMVNPSMLTSGMTIDLYMFFPYYGG   100
 101  LYNYTTISVNGYLGFATVLDQGPTINVGPETTDWPRQEDPAMIAPYLCKQ   150
 151  QVPQQGNPARRAGVYYRLLLRQSLFGRESNSNLNLGGTLQQNAFFGQQAS   200
 201  QACPGTADSYVRCDSNSDYFLDQMMIWVQEGVAGGAMFRADAAVVVTWYN   250
 251  TASAISGRSDIDAGQTGTYQVIWLTDSTARLSYVIINYDRLGFDAQDFRG   300
 301  NSRSGRCRAVFNGGNHTGTVEVDPTQPYKNTPKVLAQRSGVPHMVRGRYM   350
 351  FRVDDVVRPAGCSNKTGGTYPIMIYPNIVNMLGDMTVDVNACCLDRTQTY   400
 401  IMMIEEREVATCQVINPAIARCSLPRIYDWGTKTVYFQPESRGANDEKAF   450
 451  VGYIYFVPPTLDPMRLDIGNIYEWYKNPMTNYLMPITWYPRNFTNPDILT   500
 501  NGNNMGVRISDDSMYGVQLGLYIVGYREFKDDEIKKFRPEYRTLARITTY   550
 551  SNQNNANYRWMPQEEVINTNQVQQWYLTDWERMHTLYTYRVGFFKLAPIN   600
 601  PNDANGTQLLPGLVSAPISLHWLWTPENQQFATLTLNQQDRDQRIEFVKE   650
 651  KSREMCHDWYDEDGALWNFIRDTETNTSCPCIETQALLDLGRFMPHPRCS   700
 701  QMFRDITCTTVIGSKNCYMSSSNIYSSYAGNGNTFNNMDTNRFMTHYGQV   750
 751  CCYDESGYLMQTPYQPVIKTQREYFYNPGYPLRAYEFGTAPYMGQFEVPG   800
 801  LSVFHNDYMPYFLCCKFADFRCQMFYWRRPSSACQQYQPPAIGHAQGAGV   850
 851  FQTIDNDKFIFNQPGVFNFLYIPQSVRTPEVRIQTRLERYPNRKVDFGLL   900
 901  GRYISQYELVQPTNATVITGIALEATGTERVIVMTRKDTRRFRYRTNIIV   950
 951  GNILRYFDTIRLQRFRGVLIYVNNVERGQPEIYVVLEEAQIGVKVTESYA  1000
1001  LDIDRLPNYQESMGMLDIQISVSPQYGVRPDGDKTQETQYRQMYNLPRVS  1050
1051  GLIRPYPDQTSGSLNEGLTLNDVNSDSYRQQIINNYLVLGTGEPGTQQNQ  1100
1101  AGTLNQNMPQDNMFTTSRDEDKQFDVFPEASMRSEPVYKTAPIFDTGSYR  1150
1151  FVPQTGAMILQLLNTCRDLQNNPNTDLQPYQSIATLSYGLQCPDDPGQVL  1200
1201  TECGDSVACLYDYALLNSKVLGQEEQDAWNMFTTDRALAIRQYNSCGAIN  1250
1251  IEYPEYMMKTPALSSGYLQGDVARFECYQSHWVKGDHEYKCGIVVDYNRP  1300
1301  NEYRFEWNKGNQPWCRSRIKENYFKWLAVIAGIVGIIIVILLIFLVFWCI  1350
1351  KRKKLQESRNYSGTAAYSNNAFQNQTYETKPSRALSVGDLSTAPRTVAMP  1400
1401  PPRGTTATPMTLEPRGFSPVPSDVRGSQGMLGLNTSV               1437

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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