 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8K3K1 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MYYLALSSGFLGQAIKTSILAYLASVLLAASQGVFPRLENVGAFKKVSIV 50
51 PSHATCGYPGPSTFCRSAVAAEHAQLCAERLCIQDCPYRSASPPYTALLE 100
101 GLRSCIPADHGDLHPYSRSNSTSFIFGSHKNCPSLQAPRLAAEFTLAVWL 150
151 KPERGSTMCVLEKTADGQIVFKVTISERETMFYYRTVNGLQPPIKVMTPG 200
201 RILMKKWIHHTVQVHETEVSSFVDGLEENSTAFDTRTLRDSIMDSVPSTV 250
251 LIGQSLNGSELFVGRMQDFRLYNVSLTNREILELFSGDLPHLHIQSHCRC 300
301 PGSHPRVHPSVQQYCIPNGVEDTLQHRVSRLNPEAHPLSFINDDDVATSW 350
351 ISHVFTDITQLNQGVAISIDLENGQYQVFQITIRFSSPQPVAMRIQRKKA 400
401 DKSLWEDWQYFARNCSVWGMKNNGDLENPNSVNCLQFPEFIPFSHGNVTF 450
451 DLLTSGQKHRPGDYDFYNSSLLQEFMTATQIRLYFRGLFYPAWHTVDSRH 500
501 RYYAVDEITIIGRCQCHGHAETCDRTRRPYRCLCSPHSFTEGPQCGRCSP 550
551 LYNDKPFRSGNKVHAFNCKPCQCHGHASSCHYDASMDPFPLEYNRGGGGV 600
601 CDDCQHHTTGRNCESCQDYFYRPIGADPADPEVCKHCDCNRDGTRNGSLL 650
651 CDLVGDQCDCKRRVSGRRCFRCHIGFYGLQALDPDCCRPCDCNPSGTVDG 700
701 DITCHHNSGQCSCKANVIGLRCDRCSFGFKFLRSLNADGCEPCHCNLHGS 750
751 VNQLCDPLSGQCVCKKEAKGLRCDVCRENFYGLPWSACEVCDCNRAGTQA 800
801 GTVCDAETGQCVCKPSVGGRRCSECKEGYFNLRQNDSHLCLPCNCEKTGT 850
851 VNGSLLCDKSTGQCPCKLGVTGLRCHQCKPHRFNLTMDNPQGCQACDCDS 900
901 LGTLLGSMCDPVSGQCLCLPHRQERRCVQCQPGCYSSPSNATGCLPCLCH 950
951 TVATKNCICNSVTGHCYCPDPSTTGLSWHQCQDRYFRFDPLTGRCRPCHC 1000
1001 HVAGASNGTCDAVTGQCFCKEFVTGSKCDTCVPGASHLDVNNLLACSKTP 1050
1051 SQQPPPRGRVQSSSAINLSWSPPDFPNAHWLTYTLFRDDSEIYTTDDQHP 1100
1101 YYTQYFLDTSLSPHTAYSYYIETSNVHSSTRSIPVIYKTKPEGSEGHLNL 1150
1151 THIIPVASDSITLVWTGLSNHSGPIEKYVLSCTPVDHTEPCVSYEGPETS 1200
1201 ATIRNLVPFTQYCFSVQGCTNGSCLYSSPITVTTAQAPPQRQEPPTVWKI 1250
1251 SPTELKVEWSRPVDSNGVIIRYELYMKRWPSTEESLVFESHGWFHSHPAS 1300
1301 PSANQSENVLQDPQVSTVLSGLDPHTEYAFRVLAVNMAGSVSSAWASERT 1350
1351 GESAPVFMAAPSVSPLSPYSLSVSWEKPAENFTRGEIIGYKISMVSERSP 1400
1401 QRDVPVMCSKLVHFAESQDQSYIVQRLKPYRTYSFTVSLCASVGCVTSAL 1450
1451 GEGQTLAAAPAQLRSPMVTGVTSTTVHIRWLPPAEVNGPPPLYRLERRES 1500
1501 FLPAATAARTKGTRFMGDGYCRFPRTAHPDFIGIKASFWTRVPEGLILLA 1550
1551 LHPDNQEEYFALQLKSGRPYFLYNPQGSLVEVTTADDHSQQYSDGQWHEI 1600
1601 TAIRHQSFGQITLDEQYTDSSASLNGSSVTGGYTRLFVGGLPQGHTILQK 1650
1651 RPVRRGFVGCLKDVSILKGSSPSGTWLPLDWQSSEEQVNVHHSWEGCPTD 1700
1701 LEEGVQFLGAGFLELRSDTFHAAKDFEISLKFQTDQLNGLLLFIHNTEGL 1750
1751 DFLAMELKSGLLSFQLNSSRILTRVEVRLGRTHCDGKWNRVTIRREGSMV 1800
1801 SVGVNELTKSTSRAGDQPPLLTSPVYLGGIPQELQASYRHLTLEQGFRGC 1850
1851 VKEVAFTRGAVVNLASVSSRAVRVNQDGCLSSDSTVNCGGNDSILVYRGS 1900
1901 RQSVYESGLQPFTEYLYRVTASHKGGSVSSDWSRGRTLGSAPHSVPTPSR 1950
1951 AQSINGYSVEVAWNEPAMVKGVLEKYILKAYSEDSAQPHMPSASTEFNNT 2000
2001 DIRTGILTGLHPFHSYAVTLTACSRAGCTESSRALSISTPQEAPQEVQAP 2050
2051 VAEALPNSLSFFWSPPRQANGIITQYSLYMDGRLVYTGKGQNYTVTDLRV 2100
2101 FTAYEITVGACTRAGCTNSSRVILHTAQLPPERVDPPVLAILDSRTVHIQ 2150
2151 WKQPRQLNGILERYILYTLNPTHNSTVWDVVYNSTENLQTHLLYHLSPGC 2200
2201 LYLIKLGACTGGGCTTSEPSQALMDETVPEGVPAPRAHSHSPDSFNISWT 2250
2251 EPGHPNGVITTYELYLDGTLIHNSSELSCHAYGFDPGSLHTFQVQACTAK 2300
2301 GCALGPLVENRTLEAPPEGTVNLFVKPEGSREAAVRWDAPPHPNGRLTYS 2350
2351 VLITGNFYADQAGDNYTLLSSTKTVHSSKGDRLWVLVDRLVPCSNYTVQV 2400
2401 NASNSQGSVLSDRVSVEMPPGAPDGLLSPRLAAATPTSLQVVWSTPARNN 2450
2451 APGSPRYQLQMRPDPSTRGLLELFPIPSALLSYEVTGLQPFTVYEFRLVA 2500
2501 TNGFGSAYSDWTPLMTTEDKPGPMDAPVLNVKAGMMSVAWRKPTECNGAI 2550
2551 THYNIYQHGRLYLTVSGGVTNCTVVHLRPHTAYQFQIEACSSKGCSMSPA 2600
2601 SETVWTLPGTPEGIPGPELLPYTPTKIIVSWQPPTHLDGLVENITIERRV 2650
2651 KEQEEVRSLVILPRSQAVRFIDNDPALRPWTHYEYRVLGSTLNGGTNSSA 2700
2701 WVEVTTRPSRPSGVQPPTVHVLGPDAVEVTWKAPLIRNGDIVSYEIRMPD 2750
2751 PLIEITNVTSFVLSHLVKHLIPFTNYSVSIVACSGGHGYLGGCTESLPTF 2800
2801 ATTHPALPQELTPLSISLLGQSYVGISWQPPSKPNGPNLRYELLRRKIQQ 2850
2851 PLASNPPEDLNLWHNIYSGTRRFYEDKGLSRFTTYEYKLFVHNSLGFTPS 2900
2901 QEVTVTTLAGSPERGATVTASILNHTAIDVRWKRPTFQDLQGDVEYYTLF 2950
2951 WSSGTSVESLKIFPDVDFHVIGHLAPNVEYQVFLLVFNGVHAINSTVVRV 3000
3001 TTWEEEPRGMRPPEVVIINSTAVRVIWTSPSNPNAVITESSVYANNELHK 3050
3051 AGAGAPGSFTLEDLSPFTIYDIQVEVCTKDACVKSSGTQVSTAEDTPSGI 3100
3101 SIPIIRDITSRSLQIDWTAPGNPNGIILGYDVLRKTWRLCSETQKLTDKP 3150
3151 RDELCKAVKCQYPGNVCGHTCYSPGTKVCCDGLLYDPQPGYSCCEEKYIA 3200
3201 LLPNSTGVCCGGRQREAQPDHQCCSGHYIRILPGEICCPDERHNRVSVGF 3250
3251 GDACCGTMPYATSGSQVCCAGKLQDGYRRQCCGGEMVSQDFKCCGGGEEG 3300
3301 MVYSSLPGMLCCGQDYVNMSDTICCSASSGDSKAHVRGSDPMPVRCCHTE 3350
3351 LIPESQQCCDGVGYNPVKYVCSDEISAGMATEETRVCATVCPATMRATAH 3400
3401 CGQCDFNATTHICTVSRGPLNPIGKETAEGLCSTAEEIVHSGDENTRSFI 3450
3451 DTDLEPSTVYEYRVSVWNSYGRGFSQSVRASTREDVPQGVTAPRWARTGN 3500
3501 HEDVIFLTWKEPTQSNGPITHYILLRDGRERFQGAALSFTDTQGIQPLQE 3550
3551 YSYQLKACTAAGCADSCKVVATATRGVLESVPPPNITAQSPETLHLSWSV 3600
3601 PEKRNDAIKEYQLWLDGKGLIYTDTNDRRQHTVTGLQPHTNYSFTLSACT 3650
3651 SVGCTSSEPSVGQTLQAAPQGVWVTPRHIIINSTTVELYWNPPERPNGVI 3700
3701 SQYRLRRNGSLLLVGGRDDQSFTDKNLEPNSRYIYTLEARTGGGSSLSEE 3750
3751 YLVQMPMWTPEDVHPPCNVTVLGSDSIFVAWPAPGILLPKIPVEYSILLS 3800
3801 GGNMMLLTFSVGLRQSAYLKNLAPFTQYEIRIQACQEGCGVSPGTHVRTL 3850
3851 EAAPVGLMPPLLKALGSHCIEVKWTPPTRPNGIITSYVIHRRPADTEEES 3900
3901 LLFVWSEGALEFTDDTDTLRPFTLYEYRVRAWNSKGVVDSPWSSVQTLEA 3950
3951 PPQDLPAPWVQVTSAHSVLLNWTEPEAPNGLISQYHVIYQERPDEAAPGS 4000
4001 STVHAFTVKGSSRQAHLFGLEPFTTYHIGVAAVNRAGKVSSPWTLIKTLE 4050
4051 SAPSGLMNFTAEQREGGRALLLQWSEPVRTNGVIKAYNVFSDGLPEYSGL 4100
4101 GRQFLFRRLAPFTLYILTLEACTAAGCAHSVPQTLWTEEAPPDSQMAPTI 4150
4151 QSVEPTSVRLHWSQPANPNGKIIRYEVIRRRLQGEDWGNRTVQADENTVF 4200
4201 TEYNTEGNGWVCTDTGLQPWGLYSYRICTWNSAGHTCSSWSVVRTSQAPP 4250
4251 DGLSPPEVSYVSTSPLQLLISWFAPRHTNGVIQSYRLQRNGVFAAASFNS 4300
4301 STFSYTDGQLLPFTTYSYAVLACTGGGCCTSEPTNITTPEASPAGVSPPV 4350
4351 LWAIGAHQINVSWSPPSVPNGKIAKYLLHCDGEEHLAGQDLSLLLSNLRP 4400
4401 FTQYNVSLVACTKGGCTASRVASAWTMEAPPEDMDPPTLHVMGPESIEIT 4450
4451 WAPPRNPHGQIRSYELRRDGAIVYIGLETRYHDFILTPGVQYGYTVTATN 4500
4501 SRGSVLSPLVKGQTSPSAPSGLQPPKLRAGEALELLVNWNPPVRTNGKIT 4550
4551 NYTLFIRELLEGEIRTMCINTTHSSFGTRSLAVKHLKPFHRYEVRVQACT 4600
4601 ALGCTSSEWTPTQTSEIPPLLQPAPHLEVQTAAGGFQPIVAVWWAGPLQP 4650
4651 HGKIVRFELYRRQTASWPGTSSPLLIYNGSLSSFTDRELLPFTEYEYQVW 4700
4701 AVNSAGKVASNWTWCRTGPAPPEGLKAPTFHTVSSTQAVVNISAPSKPNG 4750
4751 NISLFRVFSNSSGTHVMLSEGMATQQTLHDLRPFTTYAIGVEACTCFNCC 4800
4801 SRGPTAELRTHPAPPSGLSPPQVQTLGSRMASFQWAPPQLPNGVIHSYEL 4850
4851 QLHRACPPDSAPHCPPSPTERKYWGPGHRASLAGLQPNTAYGVQVVAHNE 4900
4901 AGSTASGWTSFRTKKEMPQYQALFSVDSNASTVWVDWSGTFVLNGQLKEY 4950
4951 VVTDGGRRVYSGLDTTLYIPRTVDKTFFFQVTCTTDIGSVKTPLVQYDAT 5000
5001 TGFGLVLTTPGGKKGAGTKSTEFYTDTRLPRSGTPVSIRSSQSVSVLRIP 5050
5051 SQSQLSHAYSQGSLHRSVSQLMDSPDKKALTEDSLWETIMGHSSGLCVDE 5100
5101 EELMNAIKGFSSVTKEHTAFTDTHL 5125
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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