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

NucPred

Fetching O15018 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MPITQDNAVLHLPLLYQWLQNSLQEGGDGPEQRLCQAAIQKLQEYIQLNF    50
  51  AVDESTVPPDHSPPEMEICTVYLTKELGDTETVGLSFGNIPVFGDYGEKR   100
 101  RGGKKRKTHQGPVLDVGCIWVTELRKNSPAGKSGKVRLRDEILSLNGQLM   150
 151  VGVDVSGASYLAEQCWNGGFIYLIMLRRFKHKAHSTYNGNSSNSSEPGET   200
 201  PTLELGDRTAKKGKRTRKFGVISRPPANKAPEESKGSAGCEVSSDPSTEL   250
 251  ENGPDPELGNGHVFQLENGPDSLKEVAGPHLERSEVDRGTEHRIPKTDAP   300
 301  LTTSNDKRRFSKGGKTDFQSSDCLAREEVGRIWKMELLKESDGLGIQVSG   350
 351  GRGSKRSPHAIVVTQVKEGGAAHRDGRLSLGDELLVINGHLLVGLSHEEA   400
 401  VAILRSATGMVQLVVASKENSAEDLLRLTSKSLPDLTSSVEDVSSWTDNE   450
 451  DQEADGEEDEGTSSSVQRAMPGTDEPQDVCGAEESKGNLESPKQGSNKIK   500
 501  LKSRLSGGVHRLESVEEYNELMVRNGDPRIRMLEVSRDGRKHSLPQLLDS   550
 551  SSASQEYHIVKKSTRSLSTTQVESPWRLIRPSVISIIGLYKEKGKGLGFS   600
 601  IAGGRDCIRGQMGIFVKTIFPNGSAAEDGRLKEGDEILDVNGIPIKGLTF   650
 651  QEAIHTFKQIRSGLFVLTVRTKLVSPSLTPCSTPTHMSRSASPNFNTSGG   700
 701  ASAGGSDEGSSSSLGRKTPGPKDRIVMEVTLNKEPRVGLGIGACCLALEN   750
 751  SPPGIYIHSLAPGSVAKMESNLSRGDQILEVNSVNVRHAALSKVHAILSK   800
 801  CPPGPVRLVIGRHPNPKVSEQEMDEVIARSTYQESKEANSSPGLGTPLKS   850
 851  PSLAKKDSLISESELSQYFAHDVPGPLSDFMVAGSEDEDHPGSGCSTSEE   900
 901  GSLPPSTSTHKEPGKPRANSLVTLGSHRASGLFHKQVTVARQASLPGSPQ   950
 951  ALRNPLLRQRKVGCYDANDASDEEEFDREGDCISLPGALPGPIRPLSEDD  1000
1001  PRRVSISSSKGMDVHNQEERPRKTLVSKAISAPLLGSSVDLEESIPEGMV  1050
1051  DAASYAANLTDSAEAPKGSPGSWWKKELSGSSSAPKLEYTVRTDTQSPTN  1100
1101  TGSPSSPQQKSEGLGSRHRPVARVSPHCKRSEAEAKPSGSQTVNLTGRAN  1150
1151  DPCDLDSRVQATSVKVTVAGFQPGGAVEKESLGKLTTGDACVSTSCELAS  1200
1201  ALSHLDASHLTENLPKAASELGQQPMTELDSSSDLISSPGKKGAAHPDPS  1250
1251  KTSVDTGQVSRPENPSQPASPRVTKCKARSPVRLPHEGSPSPGEKAAAPP  1300
1301  DYSKTRSASETSTPHNTRRVAALRGAGPGAEGMTPAGAVLPGDPLTSQEQ  1350
1351  RQGAPGNHSKALEMTGIHAPESSQEPSLLEGADSVSSRAPQASLSMLPST  1400
1401  DNTKEACGHVSGHCCPGGSRESPVTDIDSFIKELDASAARSPSSQTGDSG  1450
1451  SQEGSAQGHPPAGAGGGSSCRAEPVPGGQTSSPRRAWAAGAPAYPQWASQ  1500
1501  PSVLDSINPDKHFTVNKNFLSNYSRNFSSFHEDSTSLSGLGDSTEPSLSS  1550
1551  MYGDAEDSSSDPESLTEAPRASARDGWSPPRSRVSLHKEDPSESEEEQIE  1600
1601  ICSTRGCPNPPSSPAHLPTQAAICPASAKVLSLKYSTPRESVASPREKAA  1650
1651  CLPGSYTSGPDSSQPSSLLEMSSQEHETHADISTSQNHRPSCAEETTEVT  1700
1701  SASSAMENSPLSKVARHFHSPPIILSSPNMVNGLEHDLLDDETLNQYETS  1750
1751  INAAASLSSFSVDVPKNGESVLENLHISESQDLDDLLQKPKMIARRPIMA  1800
1801  WFKEINKHNQGTHLRSKTEKEQPLMPARSPDSKIQMVSSSQKKGVTVPHS  1850
1851  PPQPKTNLENKDLSKKSPAEMLLTNGQKAKCGPKLKRLSLKGKAKVNSEA  1900
1901  PAANAVKAGGTDHRKPLISPQTSHKTLSKAVSQRLHVADHEDPDRNTTAA  1950
1951  PRSPQCVLESKPPLATSGPLKPSVSDTSIRTFVSPLTSPKPVPEQGMWSR  2000
2001  FHMAVLSEPDRGCPTTPKSPKCRAEGRAPRADSGPVSPAASRNGMSVAGN  2050
2051  RQSEPRLASHVAADTAQPRPTGEKGGNIMASDRLERTNQLKIVEISAEAV  2100
2101  SETVCGNKPAESDRRGGCLAQGNCQEKSEIRLYRQVAESSTSHPSSLPSH  2150
2151  ASQAEQEMSRSFSMAKLASSSSSLQTAIRKAEYSQGKSSLMSDSRGVPRN  2200
2201  SIPGGPSGEDHLYFTPRPATRTYSMPAQFSSHFGREGHPPHSLGRSRDSQ  2250
2251  VPVTSSVVPEAKASRGGLPSLANGQGIYSVKPLLDTSRNLPATDEGDIIS  2300
2301  VQETSCLVTDKIKVTRRHYCYEQNWPHESTSFFSVKQRIKSFENLANADR  2350
2351  PVAKSGASPFLSVSSKPPIGRRSSGSIVSGSLGHPGDAAARLLRRSLSSC  2400
2401  SENQSEAGTLLPQMAKSPSIMTLTISRQNPPETSSKGSDSELKKSLGPLG  2450
2451  IPTPTMTLASPVKRNKSSVRHTQPSPVSRSKLQELRALSMPDLDKLCSED  2500
2501  YSAGPSAVLFKTELEITPRRSPGPPAGGVSCPEKGGNRACPGGSGPKTSA  2550
2551  AETPSSASDTGEAAQDLPFRRSWSVNLDQLLVSAGDQQRLQSVLSSVGSK  2600
2601  STILTLIQEAKAQSENEEDVCFIVLNRKEGSGLGFSVAGGTDVEPKSITV  2650
2651  HRVFSQGAASQEGTMNRGDFLLSVNGASLAGLAHGNVLKVLHQAQLHKDA  2700
2701  LVVIKKGMDQPRPSARQEPPTANGKGLLSRKTIPLEPGIGRSVAVHDALC  2750
2751  VEVLKTSAGLGLSLDGGKSSVTGDGPLVIKRVYKGGAAEQAGIIEAGDEI  2800
2801  LAINGKPLVGLMHFDAWNIMKSVPEGPVQLLIRKHRNSS             2839

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.