 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8IZT6 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MANRRVGRGCWEVSPTERRPPAGLRGPAAEEEASSPPVLSLSHFCRSPFL 50
51 CFGDVLLGASRTLSLALDNPNEEVAEVKISHFPAADLGFSVSQRCFVLQP 100
101 KEKIVISVNWTPLKEGRVREIMTFLVNDVLKHQAILLGNAEEQKKKKRSL 150
151 WDTIKKKKISASTSHNRRVSNIQNVNKTFSVSQKVDRVRSPLQACENLAM 200
201 NEGGPPTENNSLILEENKIPISPISPAFNECHGATCLPLSVRRSTTYSSL 250
251 HASENRELLNVHSANVSKVSFNEKAVTETSFNSVNVNGQRGENSKLSLTP 300
301 NCSSTLNITQSQIHFLSPDSFVNNSHGANNELELVTCLSSDMFMKDNSQP 350
351 VHLESTIAHEIYQKILSPDSFIKDNYGLNQDLESESVNPILSPNQFLKDN 400
401 MAYMCTSQQTCKVPLSNENSQVPQSPEDWRKSEVSPRIPECQGSKSPKAI 450
451 FEELVEMKSNYYSFIKQNNPKFSAVQDISSHSHNKQPKRRPILSATVTKR 500
501 KATCTRENQTEINKPKAKRCLNSAVGEHEKVINNQKEKEDFHSYLPIIDP 550
551 ILSKSKSYKNEVTPSSTTASVARKRKSDGSMEDANVRVAITEHTEVREIK 600
601 RIHFSPSEPKTSAVKKTKNVTTPISKRISNREKLNLKKKTDLSIFRTPIS 650
651 KTNKRTKPIIAVAQSSLTFIKPLKTDIPRHPMPFAAKNMFYDERWKEKQE 700
701 QGFTWWLNFILTPDDFTVKTNISEVNAATLLLGIENQHKISVPRAPTKEE 750
751 MSLRAYTARCRLNRLRRAACRLFTSEKMVKAIKKLEIEIEARRLIVRKDR 800
801 HLWKDVGERQKVLNWLLSYNPLWLRIGLETTYGELISLEDNSDVTGLAMF 850
851 ILNRLLWNPDIAAEYRHPTVPHLYRDGHEEALSKFTLKKLLLLVCFLDYA 900
901 KISRLIDHDPCLFCKDAEFKASKEILLAFSRDFLSGEGDLSRHLGLLGLP 950
951 VNHVQTPFDEFDFAVTNLAVDLQCGVRLVRTMELLTQNWDLSKKLRIPAI 1000
1001 SRLQKMHNVDIVLQVLKSRGIELSDEHGNTILSKDIVDRHREKTLRLLWK 1050
1051 IAFAFQVDISLNLDQLKEEIAFLKHTKSIKKTISLLSCHSDDLINKKKGK 1100
1101 RDSGSFEQYSENIKLLMDWVNAVCAFYNKKVENFTVSFSDGRVLCYLIHH 1150
1151 YHPCYVPFDAICQRTTQTVECTQTGSVVLNSSSESDDSSLDMSLKAFDHE 1200
1201 NTSELYKELLENEKKNFHLVRSAVRDLGGIPAMINHSDMSNTIPDEKVVI 1250
1251 TYLSFLCARLLDLRKEIRAARLIQTTWRKYKLKTDLKRHQEREKAARIIQ 1300
1301 LAVINFLAKQRLRKRVNAALVIQKYWRRVLAQRKLLMLKKEKLEKVQNKA 1350
1351 ASLIQGYWRRYSTRQRFLKLKYYSIILQSRIRMIIAVTSYKRYLWATVTI 1400
1401 QRHWRAYLRRKQDQQRYEMLKSSTLIIQSMFRKWKQRKMQSQVKATVILQ 1450
1451 RAFREWHLRKQAKEENSAIIIQSWYRMHKELRKYIYIRSCVVIIQKRFRC 1500
1501 FQAQKLYKRRKESILTIQKYYKAYLKGKIERTNYLQKRAAAIQLQAAFRR 1550
1551 LKAHNLCRQIRAACVIQSYWRMRQDRVRFLNLKKTIIKFQAHVRKHQQRQ 1600
1601 KYKKMKKAAVIIQTHFRAYIFAMKVLASYQKTRSAVIVLQSAYRGMQARK 1650
1651 MYIHILTSVIKIQSYYRAYVSKKEFLSLKNATIKLQSTVKMKQTRKQYLH 1700
1701 LRAAALFIQQCYRSKKIAAQKREEYMQMRESCIKLQAFVRGYLVRKQMRL 1750
1751 QRKAVISLQSYFRMRKARQYYLKMYKAIIVIQNYYHAYKAQVNQRKNFLQ 1800
1801 VKKAATCLQAAYRGYKVRQLIKQQSIAALKIQSAFRGYNKRVKYQSVLQS 1850
1851 IIKIQRWYRAYKTLHDTRTHFLKTKAAVISLQSAYRGWKVRKQIRREHQA 1900
1901 ALKIQSAFRMAKAQKQFRLFKTAALVIQQNFRAWTAGRKQCMEYIELRHA 1950
1951 VLVLQSMWKGKTLRRQLQRQHKCAIIIQSYYRMHVQQKKWKIMKKAALLI 2000
2001 QKYYRAYSIGREQNHLYLKTKAAVVTLQSAYRGMKVRKRIKDCNKAAVTI 2050
2051 QSKYRAYKTKKKYATYRASAIIIQRWYRGIKITNHQHKEYLNLKKTAIKI 2100
2101 QSVYRGIRVRRHIQHMHRAATFIKAMFKMHQSRISYHTMRKAAIVIQVRC 2150
2151 RAYYQGKMQREKYLTILKAVKVLQASFRGVRVRRTLRKMQTAATLIQSNY 2200
2201 RRYRQQTYFNKLKKITKTVQQRYWAMKERNIQFQRYNKLRHSVIYIQAIF 2250
2251 RGKKARRHLKMMHIAATLIQRRFRTLMMRRRFLSLKKTAILIQRKYRAHL 2300
2301 CTKHHLQFLQVQNAVIKIQSSYRRWMIRKRMREMHRAATFIQSTFRMHRL 2350
2351 HMRYQALKQASVVIQQQYQANRAAKLQRQHYLRQRHSAVILQAAFRGMKT 2400
2401 RRHLKSMHSSATLIQSRFRSLLVRRRFISLKKATIFVQRKYRATICAKHK 2450
2451 LYQFLHLRKAAITIQSSYRRLMVKKKLQEMQRAAVLIQATFRMYRTYITF 2500
2501 QTWKHASILIQQHYRTYRAAKLQRENYIRQWHSAVVIQAAYKGMKARQLL 2550
2551 REKHKASIVIQSTYRMYRQYCFYQKLQWATKIIQEKYRANKKKQKVFQHN 2600
2601 ELKKETCVQAGFQDMNIKKQIQEQHQAAIIIQKHCKAFKIRKHYLHLRAT 2650
2651 VVSIQRRYRKLTAVRTQAVICIQSYYRGFKVRKDIQNMHRAATLIQSFYR 2700
2701 MHRAKVDYETKKTAIVVIQNYYRLYVRVKTERKNFLAVQKSVRTIQAAFR 2750
2751 GMKVRQKLKNVSEEKMAAIVNQSALCCYRSKTQYEAVQSEGVMIQEWYKA 2800
2801 SGLACSQEAEYHSQSRAAVTIQKAFCRMVTRKLETQKCAALRIQFFLQMA 2850
2851 VYRRRFVQQKRAAITLQHYFRTWQTRKQFLLYRKAAVVLQNHYRAFLSAK 2900
2901 HQRQVYLQIRSSVIIIQARSKGFIQKRKFQEIKNSTIKIQAMWRRYRAKK 2950
2951 YLCKVKAACKIQAWYRCWRAHKEYLAILKAVKIIQGCFYTKLERTRFLNV 3000
3001 RASAIIIQRKWRAILPAKIAHEHFLMIKRHRAACLIQAHYRGYKGRQVFL 3050
3051 RQKSAALIIQKYIRAREAGKHERIKYIEFKKSTVILQALVRGWLVRKRFL 3100
3101 EQRAKIRLLHFTAAAYYHLNAVRIQRAYKLYLAVKNANKQVNSVICIQRW 3150
3151 FRARLQEKRFIQKYHSIKKIEHEGQECLSQRNRAASVIQKAVRHFLLRKK 3200
3201 QEKFTSGIIKIQALWRGYSWRKKNDCTKIKAIRLSLQVVNREIREENKLY 3250
3251 KRTALALHYLLTYKHLSAILEALKHLEVVTRLSPLCCENMAQSGAISKIF 3300
3301 VLIRSCNRSIPCMEVIRYAVQVLLNVSKYEKTTSAVYDVENCIDILLELL 3350
3351 QIYREKPGNKVADKGGSIFTKTCCLLAILLKTTNRASDVRSRSKVVDRIY 3400
3401 SLYKLTAHKHKMNTERILYKQKKNSSISIPFIPETPVRTRIVSRLKPDWV 3450
3451 LRRDNMEEITNPLQAIQMVMDTLGIPY 3477
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.) |
Go back to the NucPred Home Page.