 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q80T79 from www.uniprot.org...
The NucPred score for your sequence is 0.48 (see score help below)
1 MKGSRKGESRAKESKPREPGTRRCAKCGRLDFILKKKMGIKSGFTFWNLV 50
51 FLLTLSCVKGFIYTCGGTLKGLNGTIESPGFPYGYPNGANCTWVIIAEER 100
101 NRIQIVFQSFALEEEYDYLSLYDGHPHPTNFRTRLTGFHLPPPVTSTKSV 150
151 FSLRLTSDFAVSAHGFKVYYEELQSSSCGNPGVPPKGVLYGTRFDVGDKI 200
201 RYSCVTGYILDGHPQLTCIANSVNTASWDFPVPICRAEDACGGTMRGSSG 250
251 IISSPGFPNEYHNNADCTWTIVAEPGDTISLIFTDFQMEEKYDYLEIEGS 300
301 EPPTIWLSGMNIPPPIISNKNWLRLHFVTDSNHRYRGFSAPYQGSSPLTL 350
351 TASIGELEEHIRTATGAIDVASTPADVTVSSVTAVTSHRLSEEQRVQVRS 400
401 LSDSGLDPNTPEDQLSPHQADTQSTSRRPRNAEQIERTKELAVVTHRVKK 450
451 AIDFKSRGFKLFPGKDNSNKFSLLNEGGIKTASNLCPDPGEPENGKRFGS 500
501 DFSLGSTVQFSCDEDYVLQGAKSITCQRIAEVFAAWSDHRPVCKVKTCGS 550
551 NLQGPSGTFTSPNFPFQYDSNAQCVWVITAVNTNKVIQINFEEFDLEIGY 600
601 DTLTIGDGGEVGDPRTVLQVLTGSFVPDLIVSMRSQMWLHLQTDESVGSV 650
651 GFKVNYKEIEKESCGDPGTPLYGIREGDGFSNRDVLRFECQFGFELIGEK 700
701 SIVCQENNQWSANIPICIFPCLSNFTAPMGTVLSPDYPEGYGNNLNCIWT 750
751 IISDPGSRIHLSFNDFDLESQFDFLAVKDGDSPDSPILGTFTGAEVPSHL 800
801 TSNSHILRLEFQADHSMSGRGFNITYNTFGHNECPDPGIPINARRFGDNF 850
851 QLGSSISVICEEGFIKTQGTETITCILMDGKVMWSGPIPRCGAPCGGHFS 900
901 APSGVILSPGWPGYYKDSLNCEWVIEAEPGHSIKITFERFQTELNYDVLE 950
951 VHDGPNLLSPLLGSYNGTQVPQFLFSSSNFIYLLFTTDNSRSNNGFKIHY 1000
1001 ESVTVNTYSCLDPGIPVHGRRYGHDFSIGSTVSFSCDPGYRLSHEEPLLC 1050
1051 EKNHWWSHPLPTCDALCGGDVRGPSGTILSPGYPEFYPNSLNCTWTVDVT 1100
1101 HGKGVQFNFHTFHLEDHHDYLLITENGSFTQPLARLTGSELPSTINAGLY 1150
1151 GNFRAQLRFISDFSISYEGFNITFSEYNLEPCEDPGIPQYGSRVGFSFGV 1200
1201 GDTLTFSCSLGYRLEGSSEIICLGGGRRVWSAPLPRCVAECGASATNNEG 1250
1251 ILLSPNYPLNYENNHECIYSLQVQAGKGINISARTFHLAQGDVLKIYDGK 1300
1301 DKTTHLLGAFTGASMRGLTLSSTSNQLWLEFNSDSEGTDEGFQLVYTSFE 1350
1351 LSHCEDPGIPQFGYKISDQGHFAGSTIIYGCNPGYTLHGSSLLKCMTGER 1400
1401 RAWDYPLPSCIAECGGRFKGESSGRILSPGYPFPYDNNLRCMWMIEVDPG 1450
1451 NIVSLQFLAFDTEASHDILRVWDGPPENEMLLKEVSGSLIPDGIHSTLNI 1500
1501 VTIQFDTDFYISKSGFAIQFSSSVATACRDPGVPMNGTRNGDGREPGDTV 1550
1551 VFQCDPGYELQGQERITCIQVENRYFWQPSPPVCIAPCGGNLTGSSGFIL 1600
1601 SPNFPHPYPHSRDCDWTISVNTDYVISLAFISFSIEPNYDFLYIYDGPDS 1650
1651 NSPLIGSFQDSKLPERIESSSNTMHLAFRSDGSVSYTGFHLEYKAKLRES 1700
1701 CFDPGNIMNGTRLGMDYKLGSTVTYYCDAGYVLQGYSTLTCIMGDDGRPG 1750
1751 WNRVLPSCHAPCGSRSTGSEGTVLSPNYPKNYSVDHNCVYSIAVPKEFVV 1800
1801 FGQFVFFQTSLHDVVEVFDGPTQQSPLLSSLSGSHSGESLPLSSGNQITI 1850
1851 RFTSVGPITAKGFHFVYQAVPRTSSTQCSSVPEPRFGRRIGNDFAVGSLV 1900
1901 LFECNPGYILHGSRAIRCETVPNSLAQWNDSLPTCIVPCGGILTKRKGTI 1950
1951 LSPGYPEPYDNNLNCVWKITVPEGAGIQVQVVSFATEHNWDSLDFYDGGD 2000
2001 NNAPRLGSYSGTTIPHLLNSTSNNLYLNFQSDISVSAAGFHLEYTAIGLD 2050
2051 SCPEPQTPSSGIKVGDRYMVGDVVSFQCDQGYSLQGHSHITCMPGPVRRW 2100
2101 NYPIPICLAQCGGAMSDFSGVILSPGFPGNYPSSLDCTWTIKLPIGFGVH 2150
2151 LQFVNFSTETIHDYLEVRSGSSEISTVIGRLSGPQIPSSLFSTTHETSLY 2200
2201 FHSDYSQNKQGFHIVYQAYQLQSCPDPRPFRNGFVIGNDFTVGQTISFEC 2250
2251 FPGYTLIGNSALTCLHGVSRNWNHPLPRCEALCGGNITAMNGTIYSPGYP 2300
2301 DEYPNFQDCFWLVRVPPGNGIYINFTVLQTEPIYDFITVWDGPDQNSPQI 2350
2351 GQFSGNTALESVYSTSNQILIKFHSDFTTSGFFVLSYHAYQLRVCQPPPP 2400
2401 VPNAEILTEDDEFEIGDIIRYQCLPGFTLVGNAILTCRLGERLQMDGAPP 2450
2451 VCQVLCPANELRLDSTGVILSPGYPDSYPNLQMCAWSISVEKGYNISMFV 2500
2501 EFFQTEKEFDVLQVYDGPNIQSPVLISLSGDYSAAFNVTSNGHEVFLQWS 2550
2551 ADHGNNKKGFRIRYIAFYCSTPESPPHGYIISQTGGQLNSVVRWACDRGF 2600
2601 RLVGKSSAVCRKSSYGYHSWDAPVPACQAISCGIPKAPTNGGILTTDYLV 2650
2651 GTRVTYFCNDGYRLSSKELTTATCQSDGTWSNHNKTPRCVVVTCPSINSF 2700
2701 TLDHGRWRIVNGSHYEYKTKVVFSCDPGYHGLGPASIECLPNGTWSWRTE 2750
2751 RPYCQIISCGELPTPPNGNKIGTQTSYGSTAIFTCDLGFMLVGSAVRECL 2800
2801 SSGLWSGSETRCLAGHCGIPELIVNGQVIGENYGYRDTVVYQCNPGFRLI 2850
2851 GSSVRICQQDHNWSGQLPSCVPVSCGHPGSPIYGRTSGNGFNFNDVVTFS 2900
2901 CNIGYLMQGPTKAQCQANRQWSHPPPVCKVVNCSDPGIPANSKRESKIEH 2950
2951 GNFTYGTVVFYDCNPGYFLFGSSVLICQPNGQWDKPLPECIMIDCGHPGI 3000
3001 PPNAVLSGEKYTFGSTVHYSCTGKRSLLGQASRTCQLNGHWSGSQPHCSG 3050
3051 DTTGTCGDPGTPGHGSRQESDFRTKSTVRFACDTGYILYGSEERTCLSNG 3100
3101 SWTGRQPECKAVQCGNPGTTANGKVFRIDGTTFSSSVIYSCLEGYILSGP 3150
3151 SVRQCTANGTWSGSLPNCTIISCGDPGIPANGLRYGDDFVVGQNVSYMCQ 3200
3201 PGYTIELNGSRVRTCTTNGTWSGVMPTCRAVTCSTPPQISNGRLEGTNFD 3250
3251 WGFSISYICSAGYELSFPAVLTCVGNGTWSGEVPQCLPKFCGDPGIPSQG 3300
3301 KREGKSFIYQSEVSFSCNSPFILVGSSTRLCQTDGTWSGSSPHCIEPTRT 3350
3351 SCENPGVPRHGSQNNTFGFQVGSVVQFHCKKGHLLQGSTTRTCLPDLTWS 3400
3401 GIQPECIPHSCKQPESPAHANVVGMDLPSHGYTLIYTCQPGFFLAGGTEH 3450
3451 RVCRSDNTWTGKVPVCEAGSKILVKDPRPALGTPSPKLSVPDDVFAQNYI 3500
3501 WKGSYNFKGRKQPMTLTVTSFNASTGRVNATLSNSDMELLLSGVYKSQEA 3550
3551 RLMLHIYLIKVPAHASVKKMKEENWAMDGFVSAEPDGATYVFQGFIKGKD 3600
3601 YGQFGLQRLGLNTSEGSNSSNQPHGTNSSSVAIAILVPFFALIFAGFGFY 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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