 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9NB71 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MVGLLNPLKYGDHFYELYTNSTRRKMQHDRKVLTKRKSRKDKSAAAMAAA 50
51 AAAAVLEGNAGAGGLVNPLDPPLVKEQLMILPSFPVAHIELDPNASKFAV 100
101 FSAIRSTVLEAETRYSLFQEGGAPSGQSGSNQKKWSNNVNSACCMMCAHS 150
151 CMISNLLDCSCHAHMAMHGAVGPGNAGPGGPVGVLVDGRIPAPVPVVVGG 200
201 PGLPAEKRPRRDSANSDADSDTEEPTEREPVYATVPLIVGAGLRSLFELI 250
251 ADARHVHPLLCTKALKALLDVIQGQQPESFKLEPEELINPLYDLLLDLAT 300
301 MPAALNSATGAEANWSAMACAALLGLCIARGDTGKMLKAIAAMLMTPRQL 350
351 SAQIVQLPVVLATLQHTVISAALNKPTRPDFHSHGVPHNSLIDEFPVKLP 400
401 PLSTGAPITSPAMACDGVFVYLLYGGTLLKIGTGFGGSYKGHIYAQNEDF 450
451 SHERSAWLGYSGGQLYFRRTCRRSAGDQLQMVGLDTLAIKAMSPLSMLHM 500
501 REGLNYVLFTDDDSLHAICSNRDDTLVVKKLNLYHNSYNIDPPPFELPLQ 550
551 LARKKFRTLGYAAFEDELLNQYQIQRIQSAHNSFEPKLPAPCRDADVDVM 600
601 GMACGKEFGLVRASNGRVYYYGKSAALGLKCVGRTPTLKLTELVISKAAN 650
651 IVHVAVGHDGIHALLVNDDGTVFFAGTARRGEDGDSSKNRRQPKAVKPKK 700
701 MTKIDGHVVVHAACNNGTSAFVTKTGKLIMYGKDTAHCDAMGFVSELLEQ 750
751 HVTKVALGKAHCVALNAKGQLFSFGLNNKGQCGRIFNKLQPVKDVPPFAS 800
801 SSTAAACFASLLPLDKRLKLDFSTLCDYDDHNLVQGQCRVCVICRECTGY 850
851 NVSCVSALNVPLDQRLAGSICPCGHGDAGCAKCGLCAACIALQDSDEAKT 900
901 ELKPPPSDVQQRQQRSKTLIMRRKERKGELETGAAGGGAATPTDLDKDPP 950
951 RVAPLAPQLLQLTSSSPVVQVACGLHHTVVLTLAGEVYTFGSNQYGQLGS 1000
1001 GDLQPVSGPVRVQVPGAISQVAAGSNHTVLLTSKGMVYTFGNYQKGQLGR 1050
1051 LPSDYGLKPPPQDDDSPVGAGSDGGAGGSPTVAPVGMPGPERSQSPANVQ 1100
1101 PSGSKEMPPLLPVLTQRQKFLWNCSPGAVFGLGPCYGKKVTWIGANGDQT 1150
1151 FIKIDESLITAQMLPKMHVVANKKTILLIPSIPLSFHTLSINRRDGSCTA 1200
1201 HYRGQTNFVKLMQAQPEQQQPEINSNLDVAVTPVADSPAHASTSSLLAAL 1250
1251 TGTATAGVPINEQMSRSMHEARNQIFEEQLPEVGSSAAAAAVAAPGTPVS 1300
1301 AGSVPRSRRGGKQGTSSPEPIPSPPQLAFTMDPTYNVLWVFDGAARKLRC 1350
1351 HNVVASDINDSDANAATYRSLLSPELSLPDRVDSRVARSQASLNLLACLD 1400
1401 ILTSAQDNIPGCFEQPLLKQTQQTAETQAGEFQVVNRFDNFGGGWGYSGH 1450
1451 SVEAIRFSADTDIVICGFGMFGGRGEYSCKLKLFDLGGDGGGYEKEGILI 1500
1501 SETKEVPYECGARSKHHILLPKPVSAVAGRWYLVWARIAGPSSDCGSCGQ 1550
1551 ASVTTEDQVVFSFKSSKKANNGTDVNSGQIPAILYRLVTQDCKQTPAQMD 1600
1601 ADPVQRISRAFANSVSRECFESLVVLLSWSWDCFKLQLREERDRSRPLQL 1650
1651 QQSLQYLGYVIKSCLRLLRKYTIEIYPQRNSSTSVATGGGSNAAHGSGVV 1700
1701 TTAKSVQSKPNKDKNTPRVVGNAGVMAKYFGDPSTSVAPAMISSASSGGA 1750
1751 PSTSASAAVAPGSGTPVTRKTNMENIQLAECIGNVRALLIGIFCDDIFKD 1800
1801 IATDEGYELSLEILDECHLSFVACFDAFYPTSSLKWNCLCDLLAQMDRGA 1850
1851 LHSRLLSAILAGLCSPSVKLRATFSLLSAAGNERQSIISPSDNSGLPMLS 1900
1901 STDAHPYPVLVEQMIYRTQQEKSDFLSNSWTFKDVLVRLLDIIASPIRSR 1950
1951 IEAIYSRSLGSLGYPGGKDCVNQGLIDNCCHLLARVLAEIVYQTAMGEYD 2000
2001 KLFMPPRTLHSTGARFARCDVSRTWNTGNFGPDAIAFAVDRPGVAIAGAM 2050
2051 VYSGSGSYDYQLELLYDNTADLQPQHKWETLESVSGSYDQDAVHNDLAEI 2100
2101 KFDHPVHIKENARYALRLCSQGARTCSGDAGMPAVRGPCGAQFHFYACDL 2150
2151 SFNGTTPARGQLPCILYYSTPMKQDGHSASGRTGDGSNVATHLEDRIMLL 2200
2201 GPHEVSTRDTALQIAADITKKCTELLILARNAMAASCSPSDNSSNHTQTI 2250
2251 DSEHNITPIEEHMDINWANNSRTAALPTAIDPQLSTARDLGKRIESFSKG 2300
2301 LMETLKFDKRSTNPFEMEIEIGATEVEESADLRNGQSQSVSQSQSQSQSV 2350
2351 PINGNERTADFEFAEQSAQQSMPQHLHSDSEEAPLEVAGMAAGGGVSVAD 2400
2401 GSGGVAGVGSQAAAVQLLEVFNLAASNMFHTLLPLVYAHIANLACSDPKS 2450
2451 SVQILGLIKEILPHIAALNQLHVSKDQRQPEPAIFATQTSGSGNSNSSST 2500
2501 TSNHYCVVESDHPYKSASISSYRVEFPPCVQWLTIEFDPQCGTAQLEDYL 2550
2551 LLSIPMRPASQAPPVPHVDDYLEQADNNVNGAGDRRRNTGGGIAGSGAAP 2600
2601 NTHQRSASVQLTMASCCRSPGCGNAPGSAAAPSSMPLRSQDPNDREWIVV 2650
2651 KKFNTASTWLHNVLILPGNCVEFSLETASLYAQDPHNNRYGFKCLVVGYD 2700
2701 NPTSINASNSCLIRLEQELAYLGGMCSANLMKKELNLPDDKDVEDMSGIE 2750
2751 ETINTHHTLLSKGFALSEPQLTVHQALESYLPIGSQSNERQFLKDFISGA 2800
2801 PGSSGARLAAWLQPESRLDPNKCELNTITEPLRYGWPSQVTVTIRDQYGD 2850
2851 AVLVPELKVEIKAIPTGSGPNGSATGTGTSCTSVAEVSAPGPNLWMRRAS 2900
2901 RDTWGWGGMAPPPRINYEPTVKDKMVFKAITFMKPYANYSFEELRYASPV 2950
2951 QTRVTELLNAKDMEDGTFSVQWTPSSVGAYCLAVTIDGIPLEEVYRVDVK 3000
3001 EGILPPPTQRNSAQRRPQAPSKLRRFQARHSSGLRIRSHPTLQSEQVGVV 3050
3051 RVGGVISFIDEIENDDGVWLRLSTESIRQHCTMGWYPTEAWCLQFNQHLA 3100
3101 RMLLQPVTDKEVNPVRKGVGAEEDVEEQPPVTPSASGEASPEPEPDPSPV 3150
3151 LSPAKTKPGRFLSGHQSTNPFLYPAKHADLAEREAQVQEEREKEEEQVDD 3200
3201 EDADDREPEQEALPAVELLPAHIGSAIAGVVGGGAIKLQALQKWFKGDAV 3250
3251 DGPQPLTPSHSPPLAGVSVRELVRAMGGQDSPRGNGNRSQQEQDPEFSLA 3300
3301 SMRRPNYSASQTAALLSTPKHTPKRSAVVASETSGLEDELSLLQITTTTT 3350
3351 GQGEQQSELQLATTSTASSASKRNPMGPIKRAMPPSFAESIRAVFAALLW 3400
3401 HEGVVHDAMACASFLKFHPGLPKEGATVVTRRGESGDPRLQLSREQKAQQ 3450
3451 RHSVEVANAGNYLNIRPSTLETLTKSGNCSLHNRSKYRKNLLSGGGGAIN 3500
3501 SGDDTAQKLQALPEMVSVLPPALRCLVYLWEQICSGCVQIVQSNALEQRE 3550
3551 PRLLSPGSRDLNGDADTEGKEGKNSDQASAGEKDLGRKCKRKKKDDGSWC 3600
3601 EICELFLPMPVTYHMRIAHPGCGKSAKGKGYNSVGIFCEGWAGNCGEGGK 3650
3651 GASSWFLMCDPCRDRYLASCRSANNINSAARQLESSAAEGNELNLFGVKS 3700
3701 TTLIANAEVYTTMRENATFLLELCSSSSSASGAAGSLAATSSSSKRSPQQ 3750
3751 MSVVAMPVVIEHQLGNSDLKPSTSRCSRMARLSGSKFCPGVGSGAFRKSF 3800
3801 VGGPPTAPENVWLAPESFACLECLGTAGHEDLPYEMFGLGPNSNDNGYDR 3850
3851 PLSEISYESCEPNNYDMLSGSLAPGTTAAASVGGGNLSKFHRSYSMGQGW 3900
3901 ASLAQHNHPPPHHPQQQHHQQQQMNLQLQQHQAPPVDGQPKVVYRRRNNS 3950
3951 TSEGDGSLLICYPSEHLRRLVPQKLLASVSVMQTASGEGTGKDHATGTLG 4000
4001 LDQSAGQNGGGNLLLTRPAMAFITQKHELDRLRAAMRRSLRIAACRIYAL 4050
4051 QALNWLLRSVTQGVCLHDLMWWFVSSLNPTGGHQPVERGEEASEPALEHP 4100
4101 VAYTQISGRFAHLITQSLHVFLQSVADLTLHLPLGSPLQRVAIQCFGIRF 4150
4151 RQADHQFLHSSHVFGNISKILSKSDEQNDAMAVSTILKPDCDVEHNQVHS 4200
4201 VATGGSSGAGARLLCYTDLAGMFEVTVSSRPAMAESLTDNSTETFWESDE 4250
4251 EDRNKCKIIELSLTKLNYACRYLLVHIDNSRDIQNKVLNVVFYAGQSLGD 4300
4301 TNIIKSADVDPKACSWISAKICDDSCTHFRLELHGPENTLRVRQIKLLGL 4350
4351 PIGGAVGSDDSSDHKHQPHLRLSHASRIQQQICEAETLRVFRLITGQVFG 4400
4401 KLISNVSSDLVPPDSAGIGPPSGGAASTSLLADSLDLREHMVGILFSRSK 4450
4451 LSHLQKQVIVHIVHAIRKEAQRAKEDWELANLAHVLKQSPQQQTAPALAA 4500
4501 SASCESTPERSRAPDTYCFEMLSMVLALSGSVVGRSYLSQQHGLLRDLLG 4550
4551 LLHTGSDRVQRQVTALLRRILPEITPESFAELLGVQRLPPADYSIAHQSA 4600
4601 SDFDMSRLGLLDIFLAVIAKSLQLQVKVKTTVASTGPSGSGGVSGSSSGN 4650
4651 GGAVLKAGQQEKTPAFVRLWSSLDLSVQQLRSRPPTGEPGTTDPFQFDAL 4700
4701 PPRKESKRNLNQRWFLNGVISTKQAESIISLIRDLASGKLSEKWSQITKA 4750
4751 AIAESVLNLTRLEEIYRSPEHCTKTSTLWLALASLCVLERDHVEKLSSGQ 4800
4801 WSKLCDTRPLCSNHDDGETAAIIQCETCGSLCGDCDRFLHLNRKTRSHKR 4850
4851 TVCKEEEEAIRVELHESCGRTKLFWLLALADSKTLKAMVEFRDGSHTIIS 4900
4901 GPQEAVGRCRFCGLTGNSGLLEIGNVCADAQCQEYAANSCLKTKPCGHAC 4950
4951 GGVTGERKCLPCLQHVCHTRENELAEELRDPKLTQDADDMCMICFVEALS 5000
5001 CAPSIHLECGHVFHYHCCKAVLEKRWSGPRITFGFSLCPICKADIQHPLL 5050
5051 SDILEPINGLKQDVKRKALMRIKYEGVVKDTDSKNVNMTQLAMDRYAYYV 5100
5101 CFKCQKAYYGGEARCDAEIGEKFDPEELVCGGCSDVARAQMCPKHGTDFL 5150
5151 EYKCRYCCSVAVFFCFGTTHFCDTCHDDFQRLTNIPKVKLPQCPAGPKAK 5200
5201 QLLGDECPLHVMHPPTGEEFALGCGVCRNAQTF 5233
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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