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

NucPred

Fetching Q28689 from www.uniprot.org...

The NucPred score for your sequence is 0.52 (see score help below)

   1  MLDKFCNSTFWNSSLLDSPEADLPLCFEQTVLVWIPLIFLWLLAPWQLFH    50
  51  VYRSRTKRSPITKFYLAKQVLVGCLLILAVIELILVLTENSGQATIPAVR   100
 101  YTNPILYLVTWLLVLLIQHSRQSCVQKNSWFLSLFWILSILCGTFQFQTL   150
 151  IRTLLRDSNSNLAYSCLFFISYGFQILILILSAFSEKDNSSKNPSVTASF   200
 201  LSKISFSWYDSVVLKGYKRPLTLEDVWDIDEEFKAKTIVSRFEVHMAKEL   250
 251  KKARKAFQKRQQKKSQKNSRLQGLNKNQSQSQDVLVLEETKKKNKKSGTT   300
 301  KDFPKSWLVKTIFKTFYMVLLKSFLLKLVYDLLTFLNPQLLKLLITFVSD   350
 351  PNSYAWLGYIFAILLFAVALIQSICLQTYFHMCFNLGMCVGTTVMATVYK   400
 401  KALTISNLAKRQYTIGETVNLMSVDAQKLMDVTNFIHLVWSSVLQIVLSI   450
 451  YFLWVELGPSVLAGVGVMVLLIPVNGILATKNRNIQFKNMKYKDKRLRIM   500
 501  NEILSGMKILKYFAWEPSFKDQVHNLRKKELKNLRTFAYMQSVVMFLLYL   550
 551  TPVLVSVTTFSVYVLVDSNNILDAEKAFTSITLFNILRFPMSMLPNVISA   600
 601  MLQASVSVDRLEKYLSGDDLDTSAIQRDPNFDKAVQFSEASFTWDRNLEP   650
 651  TIRNVNLDIMPGQLVAVVGTVGSGKSSLMSAMLGEMENVHGHITIKGTTA   700
 701  YVPQQSWIQNGTIKDNILFGAEFDERRYQRVLEACALLPDLEILPGGDLA   750
 751  EIGEKGINLSGGQKQRISLARASYQNSDIYILDDPLSAVDAHVGKHIFNK   800
 801  VLGPNGLLNGKTRLLVTHSLHFLPQVDEIVVVENGTILEKGSYSSLLAKK   850
 851  GVFAKNLKMFVKHTDSEGEVTVNDGSEEDDDDDSGLISSIEEFPEDSISL   900
 901  TLKRENSLHRTLSRSSRSSGRRLKSLKNSLKAQNGKTPKEEEVVKGQKLI   950
 951  KKEFMETGKVKFSIYLKYLQAIGWCSIVGIIFAYVLNSVAFIGSNLWLSA  1000
1001  WTSDSNTYNGTNYPASQRDLRIGIFGVLGLAQGLTVLVASFWSASGCAHA  1050
1051  SNILHKQLLNNILRAPMSFFNTTPIGRIVNRFAGDISTVDDTLPQSLRSW  1100
1101  MMCFLAIISTLIMICMATPVFAVIIIPLAIIYVAVQVFYVATSRQLRRLD  1150
1151  SVTRSPIYSHFTETVSGLPVIRAFEHQQRFLKQNEIGIDTNQKCVSSWIT  1200
1201  SNRWLAFRLELVGNLVVFSSALMMVIYRDTLSGDVVGFVLSNALNITQTL  1250
1251  NWLVRMTSETETNIVAVERITEYIKVENEAPWVTDKRPPAGWPHKGEIQF  1300
1301  SNYQVRYRPELDLVLKGINCDIKSMEKIGVVGRTGAGKSSLTNCLFRILE  1350
1351  AAGGHITIDGIDIASIGLHDLRGKLTIIPQDPVLFSGSLRMNLDPFNNYS  1400
1401  DEEIWRALELAHLKSFVAGLQHGLSREVSEAEDNLSIGQRQLLCLGRALL  1450
1451  RKSKILVLDEATAAVDLETDHLIQTTIRNEFSHCTVITIAHRLHTIMDSD  1500
1501  KIMVLDNGNIVEYGSPEELLESAGPFSLMAKESGIENVNNTAFWAAAARD  1550
1551  AGAGRLSPGFASVT                                      1564

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.)

Go back to the NucPred Home Page.