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

NucPred

Fetching Q99244 from www.uniprot.org...

The NucPred score for your sequence is 0.46 (see score help below)

   1  MMMMMMKKMQHQRQQQEDHANEANYARGTRPPISGEGPTSQPNSSKQTVL    50
  51  SWQAAIDAARQAKAAQTMSTSAPPPVGSLSQRKRQQYAKSKKQGNSSNSR   100
 101  PARALFCLSLNNPIRRACISIVEWKPFDIFILLAIFANCVALAIYIPFPE   150
 151  DDSNSTNHNLEKVEYAFLIIFTVETFLKIIAYGLLLHPNAYVRNGWNLLD   200
 201  FVIVIVGLFSVILEQLTKETEGGNHSSGKSGGFDVKALRAFRVLRPLRLV   250
 251  SGVPSLQVVLNSIIKAMVPLLHIALLVLFVIIIYAIIGLELFIGKMHKTC   300
 301  FFADSDIVAEEDPAPCAFSGNGRQCAVNGTECRSGWVGPNGGITNFDNFA   350
 351  FAMLTVFQCITMEGWTDVLYWMNDAMGFELPWVYFVSLVIFGSFFVLNLV   400
 401  LGVLSGEFSKEREKAKARGDFQKLRENEQLEEDLKGYLDWITQAEDIDPE   450
 451  NEEEGGEEGKRNTSMPTSETESVNTENVSGEGETQGSCGSLCQAISKSKL   500
 501  SRRWRRWNRFNRRRCRAAVKSVTFYWLVIVLVFLNTLTISSEHYNQPDWL   550
 551  TQIQDIANKVLLALFTCEMLVKMYSLGLQAYFVSLFNRFDCFVVCGGITE   600
 601  TILVELELMSPLGVSVFRCVRLLRIFKVTRHWTSLSNLVASLLNSMKSIA   650
 651  SLLLLLFLFIIIFSLLGMQLFGGKFNFDETQTKRSTFDNFPQALLTVFQI   700
 701  LTGEDWNAVMYDGIMAYGGPSSSGMIVCIYFIILFICGNYILLNVFLAIA   750
 751  VDNLADAESLNTAQKEEAEEKERKKIARKESLENKKNNKPEVNQIANSDN   800
 801  KVTIDDYQEETEDKDPYPPCDVPVGEEEEEEEEEPEVPAGPRPRRISELN   850
 851  MKEKIVPIPEGSAFFILSKTNPIRVGCHKLINHHIFTNLILVFIMLSSAA   900
 901  LAAEDPIRSHSFRNTILGYFDYAFTAIFTVEILLKMTTFGAFLHKGAFCR   950
 951  NYFNLLDMLVVGVSLVSFGIQSSAISVVKILRVLRVLRPLRAINRAKGLK  1000
1001  HVVQCVFVAIRTIGNIMIVTTLLQFMFACIGVQLFKGKFYRCTDEAKSNP  1050
1051  EECRGLFILYKDGDVDSPVVRERIWQNSDFNFDNVLSAMMALFTVSTFEG  1100
1101  WPALLYKAIDSNGENAGPVYNHRVEISIFFIIYIIIVAFFMMNIFVGFVI  1150
1151  VTFQEQGEKEYKNCELDKNQRQCVEYALKARPLRRYIPKNPYQYKFWYVV  1200
1201  NSSPFEYMMFVLIMLNTLCLAMQHYEQSKMFNDAMDILNMVFTGVFTVEM  1250
1251  VLKVIAFKPKGYFSDAWNTFDSLIVIGSIIDVALSEADPTESESLPLPTA  1300
1301  TPGNSEESNRISITFFRLFRVMRLVKLLSRGEGIRTLLWTFIKSFQALPY  1350
1351  VALLIAMLFFIYAVIGMQMFGKVAMRDNNQINRNNNFQTFPQAVLLLFRC  1400
1401  ATGEAWQEIMLACLPGKLCDPDSDYNPGEEYTCGSNFAIVYFISFYMLCA  1450
1451  FLIINLFVAVIMDNFDYLTRDWSILGPHHLDEFKRIWSEYDPEAKGRIKH  1500
1501  LDVVTLLRRIQPPLGFGKLCPHRVACKRLVAMNMPLNSDGTVMFNATLFA  1550
1551  LVRTALKIKTEGNLEQANEELRAVIKKIWKKTSMKLLDQVVPPAGGQCGL  1600
1601  CFLSPSRSRS                                          1610

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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