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

NucPred

Fetching Q75ZY9 from www.uniprot.org...

The NucPred score for your sequence is 0.50 (see score help below)

   1  MKAPAVLAPGILVLLFTLVQKSYGECKEALVKSEMNVNMKYQLPNFTAET    50
  51  PIQNVVLHKHHIYLGAVNYIYVLNDKDLQKVAEYKTGPVLEHPDCSPCQD   100
 101  CSHKANLSGGVWEDNINMALLVDTYYDDQLISCGSVHRGTCQRHILPPSN   150
 151  IADIQSEVHCMYSSQADEEPSQCPDCVVSALGTKVLISEKDRFINFFVGN   200
 201  TINSSDHPDHSLHSISVRRLKETQDGFKFLTDQSYIDVLPEFRDSYPIKY   250
 251  VHAFESNHFIYFLTVQRETLDAQTFHTRIIRFCSVDSGLHSYMEMPLECI   300
 301  LTEKRRKRSTREEVFNILQAAYVSKPGAHLAKQIGANLNDDILYGVFAQS   350
 351  KPDSAEPMNRSAVCAFPIKYVNEFFNKIVNKNNVRCLQHFYGPNHEHCFN   400
 401  RTLLRNSSGCEARNDEYRTEFTTALQRVDLFMGQFNQVLLTSISTFIKGD   450
 451  LTIANLGTSEGRFMQVVVSRSGLSTPHVNFRLDSHPVSPEAIVEHPLNQN   500
 501  GYTLVVTGKKITRIPLNGLGCEHFQSCSQCLSAPPFVQCGWCHDRCVHLE   550
 551  ECPTGAWTQEVCLPAIYEVFPTSAPLEGGTVLTVCGWDFGFRRNNKFDLK   600
 601  KTKVFLGNESCTLTLSESTTNMLKCTVGPAVNEHFNISIIISNGRGTAQY   650
 651  STFSYVDPIITSISPSYGPKNGGTLLTLTGKYLNSGNSRHISMGGKTCTL   700
 701  KSVSDSILECYTPAQATATEFPIKLKIDLANREMNSFSYQEDPIVYAIHP   750
 751  TKSFISGGSTITAVGKNLNSVSVLRMVIDVHETRRNFTVACQHRSNSEII   800
 801  CCTTPSLQQLNLQLPLKTKAFFMLDGIHSKYFDLIYVHNPVFKPFEKPVM   850
 851  ISIGNENVLEIKGNDIDPEAVKGEVLKVGNKSCETIYSDSKAVLCKVPND   900
 901  LLKLNNELNIEWKQAVSSTVLGKVIVQPDQNFTGLIAGVISISTIVLLLL   950
 951  GLFLWLKRKKQIKDLGSELVRYDARVHTPHLDRLVSARSVSPTTEMVSNE  1000
1001  SVDYRATFPEDQFPNSSQNGSCRQVQYPLTDLSPMLTSGDSDISSPLLQN  1050
1051  TVHIDLSALNPELVQAVQHVVIGPSSLIVHFNEVIGRGHFGCVYHGTLLD  1100
1101  NDDKKIHCAVKSLNRITDIGEVSQFLTEGIIMKDFSHPNVLSLLGICLRS  1150
1151  EGSPLVVLPYMKHGDLRNFIRNETHNPTVKDLIGFGLQVAKGMKYLASKK  1200
1201  FVHRDLAARNCMLDEKFTVKVADFGLARDMYDKEYYSVHNKTGAKLPVKW  1250
1251  MALESLQTQKFTTKSDVWSFGVLLWELMTRGAPPYPDVNTFDITVYLLQG  1300
1301  RRLLQPEYCPDPLYEVMLKCWHPRAELRPSFSELVSRISAIFSTFIGEHY  1350
1351  VHVNATYVNVKCVAPYPSLLSSQDNIDGEGDT                    1382

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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