 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9QYX7 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MGNEASLEGEGLPEGLAAAAGGAGGSGSALHPGIPAGMEADLSQLSEEER 50
51 RQIAAVMSRAQGLPKGSVPAAAAESPSMHRKQELDSSQAPQQPGKPPDPG 100
101 RPPQHGLSKSRTTDTFRSEQKLPGRSPSTISLKESKSRTDFKEEYKSSMM 150
151 PGFFSDVNPLSAVSSVVNKFNPFDLISDSEAVQEETTKKQKVAQKDQGKS 200
201 EGITKPSLQQPSPKLIPKQQGPGKEVIPQDIPSKSVSSQQAEKTKPQAPG 250
251 TAKPSQQSPAQTPAQQAKPVAQQPGPAKATVQQPGPAKSPAQPAGTGKSP 300
301 AQPPVTAKPPAQQAGLEKTSLQQPGPKSLAQTPGQGKVPPGPAKSPAQQP 350
351 GTAKLPAQQPGPQTAAKVPGPTKTPAQLSGPGKTPAQQPGPTKPSPQQPI 400
401 PAKPQPQQPVATKPQPQQPAPAKPQPQHPTPAKPQPQHPTPAKPQPQQPT 450
451 PAKPQPQQPTPAKPQPQQPTPAKPQPQHPTPAKPQPQQPGLGKPSAQQPS 500
501 KSISQTVTGRPLQAPPTSAAQAPAQGLSKTICPLCNTTELLLHTPEKANF 550
551 NTCTECQSTVCSLCGFNPNPHLTEIKEWLCLNCQMQRALGGELAAIPSSP 600
601 QPTPKAASVQPATASKSPVPSQQASPKKELPSKQDSPKAPESKKPPPLVK 650
651 QPTLHGPTPATAPQPPVAEALPKPAPPKKPSAALPEQAKAPVADVEPKQP 700
701 KTTETLTDSPSSAAATSKPAILSSQVQAQAQVTTAPPLKTDSAKTSQSFP 750
751 PTGDTITPLDSKAMPRPASDSKIVSHPGPTSESKDPVQKKEEPKKAQTKV 800
801 TPKPDTKPVPKGSPTPSGTRPTTGQATPQSQQPPKPPEQSRRFSLNLGGI 850
851 ADAPKSQPTTPQETVTGKLFGFGASIFSQASNLISTAGQQAPHPQTGPAA 900
901 PSKQAPPPSQTLAAQGPPKSTGPHPSAPAKTTAVKKETKGPAAENLEAKP 950
951 VQAPTVKKAEKDKKPPPGKVSKPPPTEPEKAVLAQKPDKTTKPKPACPLC 1000
1001 RTELNVGSQDPPNFNTCTECKNQVCNLCGFNPTPHLTEIQEWLCLNCQTQ 1050
1051 RAISGQLGDMDKMPPASSGPKASPVPAPAEPPPQKTPTAAHAKGKKKETE 1100
1101 VKAETEKQIPEKETPSIEKTPPAVATDQKLEESEVTKSLVSVLPEKKPSE 1150
1151 EEKALPADKKEKKPPAAEAPPLEEKKPIPDDQKLPPDAKPSASEGEEKRD 1200
1201 LLKAHVQIPEEGPIGKVASLACEGEQQPDTRPEDLPGATPQTLPKDRQKE 1250
1251 SRDVTQPQAEGTAKEGRGEPSKDRTEKEEDKSDTSSSQQPKSPQGLSDTG 1300
1301 YSSDGISGSLGEIPSLIPSDEKDLLKGLKKDSFSQESSPSSPSDLAKLES 1350
1351 TVLSILEAQASTLVGEKAEKKTQPQKVSPEQPQDQQKTQTPSETRDISIS 1400
1401 EEEIKESQEKKVTSKKDSAQGFPSRKEHKENPELVDDLSPRRASYDSVED 1450
1451 SSESENSPVARRKRRTSIGSSSSEEYKQEDSQGSGEDEDFIRKQIIEMSA 1500
1501 DEDASGSEDEEFIRSQLKEIGGVTESQKREETKGKGKSPAGKHRRLTRKS 1550
1551 STSFDDDAGRRHSWHDEDDETFDESPELKFRETKSQESEELVVAGGGGLR 1600
1601 RFKTIELNSTVTDKYSAESSQKKTTLYFDEEPELEMESLTDSPEDRSRGE 1650
1651 GSSSLHASSFTPGTSPTSVSSLDEDSDSSPSHKKGESKQQRKARHRSHGP 1700
1701 LLPTIEDSSEEEELREEEELLKEQEKQRELEQQQRKSSSKKSKKDKDELR 1750
1751 AQRRRERPKTPPSNLSPIEDASPTEELRQAAEMEELHRSSCSEYSPSIES 1800
1801 DPEGFEISPEKIIEVQKVYKLPTAVSLYSPTDEQSVMQKEGAQKALKSAE 1850
1851 EMYEEMMHKPHKYKAFPAANERDEVFEKEPLYGGMLIEDYIYESLVEDTY 1900
1901 NGSVDGSLLTRQDEQNGFMQQRGREQKIRLQEQIYDDPMQKITDLQKEFY 1950
1951 ELESLHSIVPQEDIVSSSYIIPESHEIVDLGSMVTSTSEEKKLLDADAAY 2000
2001 EELMKRQQMQVTDGSSLIQTTMGDDMAESTLDFDRVQDASLTSSILSGAS 2050
2051 LTDSTSSATLSIPDVKITQHFSTEEFEDEYVTDYTREIQEIIAHESLILT 2100
2101 YSEPSESATSVPPSDTPSLTSSISSVCTTDSSSPVTTLDSLTTVYTEPAD 2150
2151 VITKFKDSEEISSTYFPGSVIDYPEDIGVSLDRTITPESRTNADQIMISF 2200
2201 PGIAPSITESVATKPERPQADTISTDLPISEKELIKGKKETGDGIILEVL 2250
2251 DAYKDKREESEAELTKISLPETGLAPTPSSQTKEQPGSPHSVSGEILGQE 2300
2301 KPTYRSPSGGLPVSTHPSKSHPFFRSSSLDISAQPPPPPPPPPPPPPPPP 2350
2351 PPPPPPLPPATSPKPPTYPKRKLAAAAPVAPTAIVTAHADAIPTVEATAA 2400
2401 RRSNGLPATKICAAAPPPVPPKPSSIPTGLVFTHRPEASKPPIAPKPAVP 2450
2451 EIPVTTQKTTDTCPKPTGLPLTSNMSLNLVTSADYKLPSPTSPLSPHSNK 2500
2501 SSPRYSKSLMETYVVITLPSEPGTPTDSSAAQAITSWPLGSPPKDLVSLE 2550
2551 TVFSVVPPMTSTEIPSASQPTLYTSGALGTFSVTPAVTASLFQTVPTSLT 2600
2601 QFLPAEASKPEVSAVSSAVPSVAPRSVSIPIPPEPLALDRHQYKENGKLP 2650
2651 LIGDAIDLRTIPKSEVKVTEKCMDLSASAMDVKRQTTANEVYRRQISAVQ 2700
2701 PSIINLSAASSLGTPVTMDSKTVAVVTCTDTTIYTTGTESQVGIEHAVTS 2750
2751 PLQLTTSKHTELQYRKPSSQAFPMIRDEAPINLSLGPSTQAVTLAVTKPV 2800
2801 TVPPVGVTNGWTDSTISQGITDGEVVDLSTSKSHRTVVTMDESTSNVVTK 2850
2851 IIEDEEKPVDLTAGRRAVCCDMVYKLPFGRSCTAQQPATTLPEDRFGYRD 2900
2901 DHYQYDRSGPYGYRGIGGMKPSMSDTNLAEAGHFFYKSKNAFDYSGGTEA 2950
2951 AVDLTSGRVSTGEVMDYSSKTTGPYPETRQVISGVGISTPQYSTARMTPP 3000
3001 PGPQYGVGSVLRSSNGVVYSSVATPIPSTFAITTQPGSIFSTTVRDLSGI 3050
3051 HTTDAITSLSALHQSQPMPRSYFITTGASETDISVTSIDINASLQTITME 3100
3101 TLPAETMDSVPTLTTASEVFSEVVGEESTLLIVPDEDKQQQQLDLERELL 3150
3151 ELEKIKQQRFAEELEWERQEIQRFREQEKIMVQKKLEELQSMKQHLLYQQ 3200
3201 EEERQAQFMMRQETLAQQQLQLEQIQQLQQQLHQQLEEQKLRQIYQYNYE 3250
3251 PSGTASPQTTTEQAILEGQYVATEGSQFWATEDATTTASTVVAIEIPQSQ 3300
3301 GWYTVQSDGVTQYIAPPGILSTVSEIPLTDVVVKEEKQPKKRSSGAKVRG 3350
3351 QYDEMGESMADDPRNLKKIVDSGVQTDDEETADRTYASRRRRTKKSVDTS 3400
3401 VQTDDEDQDEWDMPSRSRRKARTGKYGDSTAEGDKTKPPSKVSSVAVQTV 3450
3451 AEISVQTEPLGTIRTPSIRARVDAKVEIIKHISAPEKTYKGGSLGCQTET 3500
3501 DPDTQSPPYMGATSPPKDKKRPTPLEIGYSSSHLRADPTVQLAPSPPKSP 3550
3551 KVLYSPISPLSPGHALEPAFVPYEKPLPDDISPQKVLHPDMAKVPPASPK 3600
3601 TAKMMQRSMSDPKPLSPTADESSRAPFQYSEGFTAKGSQTTSGTQKKVKR 3650
3651 TLPNPPPEEASTGTQSTYSTMGTASRRRMCRTNTMARAKILQDIDRELDL 3700
3701 VERESAKLRKKQAELDEEEKEIDAKLRYLEMGINRRKEALLKEREKRERA 3750
3751 YLQGVAEDRDYMSDSEVSSTRPSRVESQHGIERPRTAPQTEFSQFIPPQT 3800
3801 QTEAQLVPPTSPYTQYQYSSPALPTQAPTPYTQQSHFQQQTLYHQQVSPY 3850
3851 QTQPTFQAVATMSFTPQAQPTPTPQPSYQLPSQMMVIQQKPRQTTLYLEP 3900
3901 KITSTYEVIRNQPLMIAPVSTDNTYAVSHLGSKYNSLDLRIGLEERSSMA 3950
3951 SSPISSISADSFYADIDHHTSRNYVLIDDIGDITKGTAALSSAFSLHEKD 4000
4001 LSKTDRLLRTTETRRSQEVTDFLAPLQTSSRLHSYVKAEEDSMEDPYELK 4050
4051 LLKHQIKQEFRRGTESLDHLAGLSHYYHADTSYRHFPKSEKYSISRLTLE 4100
4101 KQAAKQLPAAILYQKQSKHKKALIDPKMSKFSPIQESRDLEPDYPTYLSS 4150
4151 STSSIGGISSRARLLQDDITFGLRKNITDQQKFMGSSLGSGLGTLGNTIR 4200
4201 SALQDEADKPYSSGSRSRPSSRPSSVYGLDLSIKRDSSSSSLRLKAQEAE 4250
4251 ALDVSFGHSSSSARTKPTSLPISQSRGRIPIVAQNSEEESPLSPVGQPMG 4300
4301 MARAAAGPLPPISADTRDQFGSSHSLPEVQQHMREESRTRGYDRDIAFIM 4350
4351 DDFQHAMSDSEAYHLRREETDWFDKPRESRLENGHGLDRKLPERLVHSRP 4400
4401 LSQHQEQILQMNGKTMHYIFPHARIKITRDSKDHTVSGNGLGIRIVGGKE 4450
4451 IPGHSGEIGAYIAKILPGGSAEHSGKLIEGMQVLEWNGIPLTSKTYEEVQ 4500
4501 SIINQQSGEAEICVRLDLNMLSDSENPQHLELHEPPKVVDKAKSPGVDPK 4550
4551 QLAAELQKVSLQQSPLVMSSVVEKGAHAHSGPTSAGSSSVPSPGQPGSPS 4600
4601 VSKKKHGGSKPTDVSKTASHPITGEIQLQINYDLGNLIIHILQARNLVPR 4650
4651 DNNGYSDPFVKVYLLPGRGQVMVVQNASVEYKRRTKYVQKSLNPEWNQTV 4700
4701 IYKSISMEQLMKKTLEVTVWDYDRFSSNDFLGEVLIDLSSTSHLDNTPRW 4750
4751 YPLKEQTESIEHGKSHSSQNSQQSPKPSVIKSRSHGIFPDPSKDMQVPTI 4800
4801 EKSHSSPGSSKSSSEGHLRSHGPSRSQSKTSVAQTHLEDAGAAIAAAEAA 4850
4851 VQQLRIQPTKPTNHRPAETSVSTGSSGSSVGSGYSVDSEGSSCVAGEPNL 4900
4901 LPIPRIGKMGQNGQDPVKQPGMGAADTEAKTQVMGEIKLALKKEMKTDGE 4950
4951 QLIVEILQCRNITYKFKSPDHLPDLYVKIYVINIATQKKVIKKKTRVCRH 5000
5001 DREPSFNETFRFSLSPAGHSLQILLFSNGGKFMKKTLIGEACIWLDKVDL 5050
5051 RKRIVNWHKLLMSPTQTH 5068
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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