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

NucPred

Fetching Q9UPA5 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MGNEVSLEGGAGDGPLPPGGAGPGPGPGPGPGAGKPPSAPAGGGQLPAAG    50
  51  AARSTAVPPVPGPGPGPGPGPGPGSTSRRLDPKEPLGNQRAASPTPKQAS   100
 101  ATTPGHESPRETRAQGPAGQEADGPRRTLQVDSRTQRSGRSPSVSPDRGS   150
 151  TPTSPYSVPQIAPLPSSTLCPICKTSDLTSTPSQPNFNTCTQCHNKVCNQ   200
 201  CGFNPNPHLTQVKEWLCLNCQMQRALGMDMTTAPRSKSQQQLHSPALSPA   250
 251  HSPAKQPLGKPDQERSRGPGGPQPGSRQAETARATSVPGPAQAAAPPEVG   300
 301  RVSPQPPQPTKPSTAEPRPPAGEAPAKSATAVPAGLGATEQTQEGLTGKL   350
 351  FGLGASLLTQASTLMSVQPEADTQGQPAPSKGTPKIVFNDASKEAGPKPL   400
 401  GSGPGPGPAPGAKTEPGARMGPGSGPGALPKTGGTTSPKHGRAEHQAASK   450
 451  AAAKPKTMPKERAICPLCQAELNVGSKSPANYNTCTTCRLQVCNLCGFNP   500
 501  TPHLVEKTEWLCLNCQTKRLLEGSLGEPTPLPPPTSQQPPVGAPHRASGT   550
 551  SPLKQKGPQGLGQPSGPLPAKASPLSTKASPLPSKASPQAKPLRASEPSK   600
 601  TPSSVQEKKTRVPTKAEPMPKPPPETTPTPATPKVKSGVRRAEPATPVVK   650
 651  AVPEAPKGGEAEDLVGKPYSQDASRSPQSLSDTGYSSDGISSSQSEITGV   700
 701  VQQEVEQLDSAGVTGPHPPSPSEIHKVGSSMRPLLQAQGLAPSERSKPLS   750
 751  SGTGEEQKQRPHSLSITPEAFDSDEELEDILEEDEDSAEWRRRREQQDTA   800
 801  ESSDDFGSQLRHDYVEDSSEGGLSPLPPQPPARAAELTDEDFMRRQILEM   850
 851  SAEEDNLEEDDTATSGRGLAKHGTQKGGPRPRPEPSQEPAALPKRRLPHN   900
 901  ATTGYEELLPEGGSAEATDGSGTLQGGLRRFKTIELNSTGSYGHELDLGQ   950
 951  GPDPSLDREPELEMESLTGSPEDRSRGEHSSTLPASTPSYTSGTSPTSLS  1000
1001  SLEEDSDSSPSRRQRLEEAKQQRKARHRSHGPLLPTIEDSSEEEELREEE  1050
1051  ELLREQEKMREVEQQRIRSTARKTRRDKEELRAQRRRERSKTPPSNLSPI  1100
1101  EDASPTEELRQAAEMEELHRSSCSEYSPSPSLDSEAEALDGGPSRLYKSG  1150
1151  SEYNLPTFMSLYSPTETPSGSSTTPSSGRPLKSAEEAYEEMMRKAELLQR  1200
1201  QQGQAAGARGPHGGPSQPTGPRGLGSFEYQDTTDREYGQAAQPAAEGTPA  1250
1251  SLGAAVYEEILQTSQSIVRMRQASSRDLAFAEDKKKEKQFLNAESAYMDP  1300
1301  MKQNGGPLTPGTSPTQLAAPVSFSTPTSSDSSGGRVIPDVRVTQHFAKET  1350
1351  QDPLKLHSSPASPSSASKEIGMPFSQGPGTPATTAVAPCPAGLPRGYMTP  1400
1401  ASPAGSERSPSPSSTAHSYGHSPTTANYGSQTEDLPQAPSGLAAAGRAAR  1450
1451  EKPLSASDGEGGTPQPSRAYSYFASSSPPLSPSSPSESPTFSPGKMGPRA  1500
1501  TAEFSTQTPSPAPASDMPRSPGAPTPSPMVAQGTQTPHRPSTPRLVWQES  1550
1551  SQEAPFMVITLASDASSQTRMVHASASTSPLCSPTETQPTTHGYSQTTPP  1600
1601  SVSQLPPEPPGPPGFPRVPSAGADGPLALYGWGALPAENISLCRISSVPG  1650
1651  TSRVEPGPRTPGTAVVDLRTAVKPTPIILTDQGMDLTSLAVEARKYGLAL  1700
1701  DPIPGRQSTAVQPLVINLNAQEHTFLATATTVSITMASSVFMAQQKQPVV  1750
1751  YGDPYQSRLDFGQGGGSPVCLAQVKQVEQAVQTAPYRSGPRGRPREAKFA  1800
1801  RYNLPNQVAPLARRDVLITQMGTAQSIGLKPGPVPEPGAEPHRATPAELR  1850
1851  SHALPGARKPHTVVVQMGEGTAGTVTTLLPEEPAGALDLTGMRPESQLAC  1900
1901  CDMVYKLPFGSSCTGTFHPAPSVPEKSMADAAPPGQSSSPFYGPRDPEPP  1950
1951  EPPTYRAQGVVGPGPHEEQRPYPQGLPGRLYSSMSDTNLAEAGLNYHAQR  2000
2001  IGQLFQGPGRDSAMDLSSLKHSYSLGFADGRYLGQGLQYGSVTDLRHPTD  2050
2051  LLAHPLPMRRYSSVSNIYSDHRYGPRGDAVGFQEASLAQYSATTAREISR  2100
2101  MCAALNSMDQYGGRHGSGGGGPDLVQYQPQHGPGLSAPQSLVPLRPGLLG  2150
2151  NPTFPEGHPSPGNLAQYGPAAGQGTAVRQLLPSTATVRAADGMIYSTINT  2200
2201  PIAATLPITTQPASVLRPMVRGGMYRPYASGGITAVPLTSLTRVPMIAPR  2250
2251  VPLGPTGLYRYPAPSRFPIASSVPPAEGPVYLGKPAAAKAPGAGGPSRPE  2300
2301  MPVGAAREEPLPTTTPAAIKEAAGAPAPAPLAGQKPPADAAPGGGSGALS  2350
2351  RPGFEKEEASQEERQRKQQEQLLQLERERVELEKLRQLRLQEELERERVE  2400
2401  LQRHREEEQLLVQRELQELQTIKHHVLQQQQEERQAQFALQREQLAQQRL  2450
2451  QLEQIQQLQQQLQQQLEEQKQRQKAPFPAACEAPGRGPPLAAAELAQNGQ  2500
2501  YWPPLTHAAFIAMAGPEGLGQPREPVLHRGLPSSASDMSLQTEEQWEASR  2550
2551  SGIKKRHSMPRLRDACELESGTEPCVVRRIADSSVQTDDEDGESRYLLSR  2600
2601  RRRARRSADCSVQTDDEDSAEWEQPVRRRRSRLPRHSDSGSDSKHDATAS  2650
2651  SSSAAATVRAMSSVGIQTISDCSVQTEPDQLPRVSPAIHITAATDPKVEI  2700
2701  VRYISAPEKTGRGESLACQTEPDGQAQGVAGPQLVGPTAISPYLPGIQIV  2750
2751  TPGPLGRFEKKKPDPLEIGYQAHLPPESLSQLVSRQPPKSPQVLYSPVSP  2800
2801  LSPHRLLDTSFASSERLNKAHVSPQKHFTADSALRQQTLPRPMKTLQRSL  2850
2851  SDPKPLSPTAEESAKERFSLYQHQGGLGSQVSALPPNSLVRKVKRTLPSP  2900
2901  PPEEAHLPLAGQASPQLYAASLLQRGLTGPTTVPATKASLLRELDRDLRL  2950
2951  VEHESTKLRKKQAELDEEEKEIDAKLKYLELGITQRKESLAKDRGGRDYP  3000
3001  PLRGLGEHRDYLSDSELNQLRLQGCTTPAGQFVDFPATAAAPATPSGPTA  3050
3051  FQQPRFQPPAPQYSAGSGGPTQNGFPAHQAPTYPGPSTYPAPAFPPGASY  3100
3101  PAEPGLPNQQAFRPTGHYAGQTPMPTTQSTLFPVPADSRAPLQKPRQTSL  3150
3151  ADLEQKVPTNYEVIASPVVPMSSAPSETSYSGPAVSSGYEQGKVPEVPRA  3200
3201  GDRGSVSQSPAPTYPSDSHYTSLEQNVPRNYVMIDDISELTKDSTSTAPD  3250
3251  SQRLEPLGPGSSGRPGKEPGEPGVLDGPTLPCCYARGEEESEEDSYDPRG  3300
3301  KGGHLRSMESNGRPASTHYYGDSDYRHGARVEKYGPGPMGPKHPSKSLAP  3350
3351  AAISSKRSKHRKQGMEQKISKFSPIEEAKDVESDLASYPPPAVSSSLVSR  3400
3401  GRKFQDEITYGLKKNVYEQQKYYGMSSRDAVEDDRIYGGSSRSRAPSAYS  3450
3451  GEKLSSHDFSGWGKGYEREREAVERLQKAGPKPSSLSMAHSRVRPPMRSQ  3500
3501  ASEEESPVSPLGRPRPAGGPLPPGGDTCPQFCSSHSMPDVQEHVKDGPRA  3550
3551  HAYKREEGYILDDSHCVVSDSEAYHLGQEETDWFDKPRDARSDRFRHHGG  3600
3601  HAVSSSSQKRGPARHSYHDYDEPPEEGLWPHDEGGPGRHASAKEHRHGDH  3650
3651  GRHSGRHTGEEPGRRAAKPHARDLGRHEARPHSQPSSAPAMPKKGQPGYP  3700
3701  SSAEYSQPSRASSAYHHASDSKKGSRQAHSGPAALQSKAEPQAQPQLQGR  3750
3751  QAAPGPQQSQSPSSRQIPSGAASRQPQTQQQQQGLGLQPPQQALTQARLQ  3800
3801  QQSQPTTRGSAPAASQPAGKPQPGPSTATGPQPAGPPRAEQTNGSKGTAK  3850
3851  APQQGRAPQAQPAPGPGPAGVKAGARPGGTPGAPAGQPGADGESVFSKIL  3900
3901  PGGAAEQAGKLTEAVSAFGKKFSSFW                          3926

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.