 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q00174 from www.uniprot.org...
The NucPred score for your sequence is 0.47 (see score help below)
1 MGHGVASIGALLVILAISYCQAELTPPYFNLATGRKIYATATCGQDTDGP 50
51 ELYCKLVGANTEHDHIDYSVIQGQVCDYCDPTVPERNHPPENAIDGTEAW 100
101 WQSPPLSRGMKFNEVNLTINFEQEFHVAYLFIRMGNSPRPGLWTLEKSTD 150
151 YGKTWTPWQHFSDTPADCETYFGKDTYKPITRDDDVICTTEYSKIVPLEN 200
201 GEIPVMLLNERPSSTNYFNSTVLQEWTRATNVRIRLLRTKNLLGHLMSVA 250
251 RQDPTVTRRYFYSIKDISIGGRCMCNGHADTCDVKDPKSPVRILACRCQH 300
301 HTCGIQCNECCPGFEQKKWRQNTNARPFNCEPCNCHGHSNECKYDEEVNR 350
351 KGLSLDIHGHYDGGGVCQNCQHNTVGINCNKCKPKYYRPKGKHWNETDVC 400
401 SPCQCDYFFSTGHCEEETGNCECRAAFQPPSCDSCAYGYYGYPNCRECEC 450
451 NLNGTNGYHCEAESGQQCPCKINFAGAYCKQCAEGYYGFPECKACECNKI 500
501 GSITNDCNVTTGECKCLTNFGGDNCERCKHGYFNYPTCSYCDCDNQGTES 550
551 EICNKQSGQCICREGFGGPRCDQCLPGFYNYPDCKPCNCSSTGSSAITCD 600
601 NTGKCNCLNNFAGKQCTLCTAGYYSYPDCLPCHCDSHGSQGVSCNSDGQC 650
651 LCQPNFDGRQCDSCKEGFYNFPSCEDCNCDPAGVIDKFAGCGSVPVGELC 700
701 KCKERVTGRICNECKPLYWNLNISNTEGCEICDCWTDGTISALDTCTSKS 750
751 GQCPCKPHTQGRRCQECRDGTFDLDSASLFGCKDCSCDVGGSWQSVCDKI 800
801 SGQCKCHPRITGLACTQPLTTHFFPTLHQFQYEYEDGSLPSGTQVRYDYD 850
851 EAAFPGFSSKGYVVFNAIQNDVRNEVNVFKSSLYRIVLRYVNPNAENVTA 900
901 TISVTSDNPLEVDQHVKVLLQPTSEPQFVTVAGPLGVKPSAIVLDPGRYV 950
951 FTTKANKNVMLDYFVLLPAAYYEAGILTRHISNPCELGNMELCRHYKYAS 1000
1001 VEVFSPAATPFVIGENSKPTNPVETYTDPEHLQIVSHVGDIPVLSGSQNE 1050
1051 LHYIVDVPRSGRYIFVIDYISDRNFPDSYYINLKLKDNPDSETSVLLYPC 1100
1101 LYSTICRTSVNEDGMEKSFYINKEDLQPVIISADIEDGSRFPIISVTAIP 1150
1151 VDQWSIDYINPSPVCVIHDQQCATPKFRSVPDSKKIEFETDHEDRIATNK 1200
1201 PPYASLDERVKLVHLDSQNEATIVIESKVDATKPNLFVILVKYYQPSHPK 1250
1251 YQVYYTLTAGKNQYDGKFDIQHCPSSSGCRGVIRPAGEGSFEIDDEFKFT 1300
1301 ITTDRSQSVWLDYLVVVPLKQYNDDLLVEETFDQTKEFIQNCGHDHFHIT 1350
1351 HNASDFCKKSVFSLTADYNSGALPCNCDYAGSTSFECHPFGGQCQCKPNV 1400
1401 IERTCGACRSRYYGFPDCKPCKCPNSAMCEPTTGECMCPPNVIGDLCEKC 1450
1451 APNTYGFHQVIGCEECACNPMGIANGNSQCDLFNGTCECRQNIEGRACDV 1500
1501 CSNGYFNFPHCEQCSCHKPGTELEVCDKIDGACFCKKNVVGRDCDQCVDG 1550
1551 TYNLQESNPDGCTTCFCFGKTSRCDSAYLRVYNVSLLKHVSITTPEFHEE 1600
1601 SIKFDMWPVPADEILLNETTLKADFTLREVNDERPAYFGVLDYLLNQNNH 1650
1651 ISAYGGDLAYTLHFTSGFDGKYIVAPDVILFSEHNALVHTSYEQPSRNEP 1700
1701 FTNRVNIVESNFQTISGKPVSRADFMMVLRDLKVIFIRANYWEQTLVTHL 1750
1751 SDVYLTLADEDADGTGEYQFLAVERCSCPPGYSGHSCEDCAPGYYRDPSG 1800
1801 PYGGYCIPCECNGHSETCDCATGICSKCQHGTEGDHCERCVSGYYGNATN 1850
1851 GTPGDCMICACPLPFDSNNFATSCEISESGDQIHCECKPGYTGPRCESCA 1900
1901 NGFYGEPESIGQVCKPCECSGNINPEDQGSCDTRTGECLRCLNNTFGAAC 1950
1951 NLCAPGFYGDAIKLKNCQSCDCDDLGTQTCDPFVGVCTCHENVIGDRCDR 2000
2001 CKPDHYGFESGVGCRACDCGAASNSTQCDPHTGHCACKSGVTGRQCDRCA 2050
2051 VDHWKYEKDGCTPCNCNQGYSRGFGCNPNTGKCQCLPGVIGDRCDACPNR 2100
2101 WVLIKDEGCQECNNCHHALLDVTDRMRYQIDSVLEDFNSVTLAFFTSQKL 2150
2151 NYYDQLADELEPKVKLLDPNSVDLSPSKKANSELESDAKSYAKQVNQTLA 2200
2201 NAFDIRERSSTTLGNITVAYDEAVKSADQAKEAIASVEALSKNLEAAAST 2250
2251 KIDAALEQAQHILGQINGTSIELTPNEQVLEKARKLYEEVNTLVLPIKAQ 2300
2301 NKSLNALKNDIGEFSDHLEDLFNWSEASQAKSADVERRNVANQKAFDNSK 2350
2351 FDTVSEQKLQAEKNIKDAGNFLINGDLTLNQINQKLDNLRDALNELNSFN 2400
2401 KNVDEELPVREDQHKEADALTDQAEQKAAELAIKAQDLAAQYTDMTASAE 2450
2451 PAIKAATAYSGIVEAVEAAQKLSQDAISAAGNATDKTDGIEERAHLADTG 2500
2501 STDLLQRARQSLQKVQDDLEPRLNASAGKVQKISAVNNATEHQLKDINKL 2550
2551 IDQLPAESQRDMWKNSNANASDALEILKNVLEILEPVSVQTPKELEKAHG 2600
2601 INRDLDLTNKDVSQANKQLDDVEGSVSKLNELAEDIEEQQHRVGSQSRQL 2650
2651 GQEIENLKAQVEAARQLANSIKVGVNFKPSTILELKTPEKTKLLATRTNL 2700
2701 STYFRTTEPSGFLLYLGNDNKTAQKNNDFVAVEIVNGYPILTIDLGNGPE 2750
2751 RITSDKYVADGRWYQAVVDRMGPNAKLTIREELPNGDVVEHSKSGYLEGS 2800
2801 QNILHVDKNSRLFVGGYPGISDFNAPPDLTTNSFSGDIEDLKIGDESVGL 2850
2851 WNFVYGDDNDQGARERDVLLEKKKPVTGLRFKGNGYVQLNATSNLKSRSS 2900
2901 IQFSFKADKDTSNGLLFFYGRDKHYMSIEMIDGAIFFNISLGEGGGVQSG 2950
2951 SQDRYNDNQWHKVQAERENRNGLLKVDDIVISRTNAPLEADLELPKLRRL 3000
3001 YFGGHPRRLNTSISLQPNFDGCIDNVVINQGVVDLTEYVTGGGVEEGCSA 3050
3051 KFSTVVSYAPHEYGFLRMNNVSSDNNLHVVLHFKTTQPNGVLFYAANHDQ 3100
3101 SSTIGLSLQDGLLKLNSMGSQLVIDDRILNDGEDHVVTVQHTQGELRLTV 3150
3151 DDVDNKRLGSPQPLILEGGDIFFAGLPDNYRTPRNALASLAYFVGCISDV 3200
3201 TVNEEIINFANSAEKKNGNINGCPPHVLAYEPSLVPSYYPSGDNEVESPW 3250
3251 SNADTLPPLKPDIESTLPPTTPTTTTTTTTTTTSTTTTSTTTTTTTPSPI 3300
3301 VIDEEKEIEAKTPQKILTTRPPAKLNLPSDERCKLPEQPNFDVDFTEAGY 3350
3351 RFYGLREQRLQINSLPVKVRRHHDIGISFRTERPNGLLIYAGSKQRDDFI 3400
3401 AVYLLDGRVTYEIRVGAQLQAKITTEAELNDGTWHTVEVVRTQRKVSLLI 3450
3451 DKLEQPGSVDLNAERSAPVLAVELPIYLGGVNKFLESEVKNLTDFKTEVP 3500
3501 YFNGCLKNIKFDAMDLETPPEEFGVVPCSEQVERGLFFNNQKAFVKIFDH 3550
3551 FDVGTEMKISFDFRPRDPNGLLFSVHGKNSYAILELVDNTLYFTVKTDLK 3600
3601 NIVSTNYKLPNNESFCDGKTRNVQAIKSKFVINIAVDFISSNPGVGNEGS 3650
3651 VITRTNRPLFLGGHVAFQRAPGIKTKKSFKGCISKVEVNQRMINITPNMV 3700
3701 VGDIWQGYCPLN 3712
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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