 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7Z407 from www.uniprot.org...
The NucPred score for your sequence is 0.53 (see score help below)
1 MKGIRKGESRAKESKPWEPGKRRCAKCGRLDFILMKKMGIKSGFTFWNLV 50
51 FLLTVSCVKGFIYTCGGTLKGLNGTIESPGFPYGYPNGANCTWVIIAEER 100
101 NRIQIVFQSFALEEEYDYLSLYDGHPHPTNFRTRLTGFHLPPPVTSTKSV 150
151 FSLRLTSDFAVSAHGFKVYYEELQSSSCGNPGVPPKGVLYGTRFDVGDKI 200
201 RYSCVTGYILDGHPQLTCIANSVNTASWDFPVPICRAEDACGGTMRGSSG 250
251 IISSPSFPNEYHNNADCTWTIVAEPGDTISLIFTDFQMEEKYDYLEIEGS 300
301 EPPTIWLSGMNIPPPIISNKNWLRLHFVTDSNHRYRGFSAPYQGSSTLTH 350
351 TTSTGELEEHNRTTTGAIAVASTPADVTVSSVTAVTIHRLSEEQRVQVTS 400
401 LRNSGLDPNTSKDGLSPHPADTQSTRRRPRHAEQIERTKELAVVTHRVKK 450
451 AIDFKSRGFKLFPGKDNSNKFSILNEGGIKTASNLCPDPGEPENGKRIGS 500
501 DFSLGSTVQFSCDEDYVLQGAKSITCQRIAEVFAAWSDHRPVCKVKTCGS 550
551 NLQGPSGTFTSPNFPFQYDSNAQCVWVITAVNTNKVIQINFEEFDLEIGY 600
601 DTLTIGDGGEVGDPRTVLQVLTGSFVPDLIVSMSSQMWLHLQTDESVGSV 650
651 GFKVNYKEIEKESCGDPGTPLYGIREGDGFSNRDVLRFECQFGFELIGEK 700
701 SIVCQENNQWSANIPICIFPCLSNFTAPMGTVLSPDYPEGYGNNLNCIWT 750
751 IISDPGSRIHLSFNDFDLESQFDFLAVKDGDSPESPILGTFTGAEVPSHL 800
801 TSNSHILRLEFQADHSMSGRGFNITYNTFGHNECPDPGIPINARRFGDNF 850
851 QLGSSISVICEEGFIKTQGTETITCILMDGKVMWSGLIPKCGAPCGGHFS 900
901 APSGVILSPGWPGYYKDSLNCEWVIEAEPGHSIKITFERFQTELNYDVLE 950
951 VHDGPNLLSPLLGSYNGTQVPQFLFSSSNFIYLLFTTDNSRSNNGFKIHY 1000
1001 ESVTVNTYSCLDPGIPVHGRRYGHDFSIGSTVSFSCDSGYRLSHEEPLLC 1050
1051 EKNHWWSHPLPTCDALCGGDVRGPSGTILSPGYPEFYPNSLNCTWTVDVT 1100
1101 HGKGVQFNFHTFHLEDHHDYLLITENGSFTQPLARLTGSDLPPTINAGLY 1150
1151 GNFRAQLRFISDFSISYEGFNITFSEYNLEPCEDPGIPQYGSRIGFNFGI 1200
1201 GDTLTFSCSSGYRLEGTSEIICLGGGRRVWSAPLPRCVAECGASATNNEG 1250
1251 ILLSPNYPLNYENNHECIYSIQVQAGKGINISARTFHLAQGDVLKIYDGK 1300
1301 DKTTHLLGAFTGASMRGLTLSSTSNQLWLEFNSDTEGTDEGFQLVYTSFE 1350
1351 LSHCEDPGIPQFGYKISDQGHFAGSTIIYGCNPGYTLHGSSLLKCMTGER 1400
1401 RAWDYPLPSCIAECGGRFKGESSGRILSPGYPFPYDNNLRCMWMIEVDPG 1450
1451 NIVSLQFLAFDTEASHDILRVWDGPPENDMLLKEISGSLIPEGIHSTLNI 1500
1501 VTIQFDTDFYISKSGFAIQFSSSVATACRDPGVPMNGTRNGDGREPGDTV 1550
1551 VFQCDPGYELQGEERITCIQVENRYFWQPSPPVCIAPCGGNLTGSSGFIL 1600
1601 SPNFPHPYPHSRDCDWTITVNADYVISLAFISFSIEPNYDFLYIYDGPDS 1650
1651 NSPLIGSFQDSKLPERIESSSNTMHLAFRSDGSVSYTGFHLEYKAKLRES 1700
1701 CFDPGNIMNGTRLGMDYKLGSTVTYYCDAGYVLQGYSTLTCIMGDDGRPG 1750
1751 WNRALPSCHAPCGSRSTGSEGTVLSPNYPKNYSVGHNCVYSIAVPKEFVV 1800
1801 FGQFVFFQTSLHDVVEVYDGPTQQSSLLSSLSGSHSGESLPLSSGNQITI 1850
1851 RFTSVGPITAKGFHFVYQAVPRTSSTQCSSVPEPRFGRRIGNEFAVGSSV 1900
1901 LFDCNPGYILHGSIAIRCETVPNSLAQWNDSLPTCIVPCGGILTKRKGTI 1950
1951 LSPGYPEPYDNNLNCVWKITVPEGAGIQVQVVSFATEHNWDSLDFYDGGD 2000
2001 NNAPRLGSYSGTTIPHLLNSTSNNLYLNFQSDISVSAAGFHLEYTAIGLD 2050
2051 SCPEPQTPSSGIKIGDRYMVGDVVSFQCDQGYSLQGHSHITCMPGPVRRW 2100
2101 NYPIPICLAQCGGAMSDFSGVILSPGFPGNYPSSLDCTWTINLPIGFGVH 2150
2151 LQFVNFSTETIHDYLEVRSGSSETSTVIGRLSGPQIPSSLFSTTHETSLY 2200
2201 FHSDYSQNKQGFHIVYQAYQLQSCPDPRPFRNGFVIGNDFTVGQTISFEC 2250
2251 FPGYTLIGNSALTCLHGVSRNWNHPLPRCEALCGGNITAMNGTIYSPGYP 2300
2301 DEYPNFQDCFWLVRVPPGNGIYINFTVLQTEPIYDFITVWDGPDQNSPQI 2350
2351 GQFSGNTALESVYSTSNQILIKFHSDFTTSGFFVLSYHAYQLRVCQPPPP 2400
2401 VPNAEILTEDDEFEIGDIIRYQCLPGFTLVGNAILTCRLGERLQMDGAPP 2450
2451 VCQVLCPANELRLDSTGVILSPGYPDSYPNLQMCAWSISVEKGYNITMFV 2500
2501 EFFQTEKEFDVLQVYDGPNIQSPVLISLSGDYSSAFNITSNGHEVFLQWS 2550
2551 ADHGNNKKGFRIRYIAFYCSTPESPPHGYIISQTGGQLNSVVRWACDRGF 2600
2601 RLVGKSSAVCRKSSYGYHAWDAPVPACQAISCGIPKAPTNGGILTTDYLV 2650
2651 GTRVTYFCNDGYRLSSKELTTAVCQSDGTWSNHNKTPRCVVVTCPSINSF 2700
2701 ILEHGRWRIVNGSHYEYKTKVVFSCDPGYHGLGPASIECLPNGTWSWRNE 2750
2751 RPYCQIISCGELPTPPNGNKIGTQTSYGSTAIFTCDLGFMLVGSAVRECL 2800
2801 SSGLWSESETRCLAGHCGIPELIVNGQVIGENYGYRDTVVYQCNPGFRLI 2850
2851 GSSVRICQQDHNWSGQLPSCVPVSCGHPGSPIYGRTSGNGFNFNDVVTFS 2900
2901 CNIGYLMQGPTKAQCQANRQWSHPPPMCKVVNCSDPGIPANSKRESKIEH 2950
2951 GNFTYGTVVFYDCNPGYFLFGSSVLICQPNGQWDKPLPECIMIDCGHPGV 3000
3001 PPNAVLSGEKYTFGSTVHYSCTGKRSLLGQSSRTCQLNGHWSGSQPHCSG 3050
3051 DATGTCGDPGTPGHGSRQESNFRTKSTVRYACDTGYILHGSEERTCLANG 3100
3101 SWTGRQPECKAVQCGNPGTTANGKVFRIDGTTFSSSVIYSCMEGYILSGP 3150
3151 SVRQCTANGTWSGTLPNCTIISCGDPGIPANGLRYGDDYVVGQNVSYMCQ 3200
3201 PGYTMELNGSRIRTCTINGTWSGVMPTCRAVTCPTPPQISNGRLEGTNFD 3250
3251 WGFSISYICSPGYELSFPAVLTCVGNGTWSGEVPQCLPKFCGDPGIPAQG 3300
3301 KREGKSFIYQSEVSFSCNFPFILVGSSTRICQADGTWSGSSPHCIEPTQT 3350
3351 SCENPGVPRHGSQNNTFGFQVGSVVQFHCKKGHLLQGSTTRTCLPDLTWS 3400
3401 GIQPECIPHSCKQPETPAHANVVGMDLPSHGYTLIYTCQPGFFLAGGTEH 3450
3451 RVCRSDNTWTGKVPICEAGSKILVKDPRPALGTPSPKLSVPDDVFAQNYI 3500
3501 WKGSYNFKGRKQPMTLTVTSFNASTGRVNATLSNSNMELLLSGVYKSQEA 3550
3551 RLMLRIYLIKVPAHASVKKMKEENWAMDGFVSAEPDGATYVFQGFIQGKD 3600
3601 YGQFGLQRLGLNMSEGSNSSNQPHGTNSSSVAIAILVPFFALIFAGFGFY 3650
3651 LYKQRTAPKTQYTGCSVHENNNGQAAFENPMYDTNAKSVEGKAVRFDPNL 3700
3701 NTVCTMV 3707
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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