 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P36022 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MCKNEARLANELIEFVAATVTGIKNSPKENEQAFIDYLHCQYLERFQFFL 50
51 GLLDGREFDTLFVFLFEELDRTIVTIDIGEEAIYDANLANKKYSTLLIIK 100
101 SRSVIVDAEPIATQISAIYLPGPVNAGNLASIITHGVSSVFGQLIKSDTK 150
151 TYSVETIDKTRRKLDDISKQFQQLHTSIETPDLLAMVPSIIKLAVSKGAT 200
201 SHDYANYLPSNDLESMRFLNILQSIANKWFLVLKQTLAIDRDIKNGSFLD 250
251 EVEFWSNFYEVLKSLIEQTQSQEFQVCLSVLTNAKRFHNLTNLLNEGSLS 300
301 DKFKLADKYNQFLSSIPIDEVRQASNLEDLQELFPVLASSLKKFRYSGYP 350
351 VQRFVVLMDKISQEVMDAILSNLSDLFQLEYGSFLGLYEKSAGMIEEWDD 400
401 IVQDVNLLIREDLRKRAPQELLIQKLTFTSASVKATLDEILSTRKRFFSL 450
451 AETIKSISPSTYHEEIQRLYHPFEQIHDISVNFRLKLEQAESEFSKNMLD 500
501 LEKKLQNTLASFMDSDHCPTEKLSYLVKFKPLMELCPRIKVKVLENQQIL 550
551 LLEIKKDIRQLETGLELLPKILHVEALNNIPPISARISYFLNVQSRIDNI 600
601 VQYLEALFGSNWNDTLEGRSISTSIVQLRKETNPHDVFLHWLGNFPEKAT 650
651 ANLLTTPILKLIRNNEDDYELKVNFDFALAAAYSELRSLTYMAFQVPSHI 700
701 VRIARTYMYLYPRAINLVELIQTFFSLSKSLSYTFYTNIFLKRNVQTVWL 750
751 LLQQILITPWESLQEESSEMSCSVHSLARLEKSIDGILSDYQILKNSEPQ 800
801 FAKEFSGLKSFDGTADDLHEVEEIISNIQAIFENLFTKGLTNVSDHISTF 850
851 NNLIISIILEKVRLNLKKMHFPKHVLKLSFNEGRITSSPSLAAMKRSLLK 900
901 DIEALLNKVVLINFLHDPDHPLSTTLTFNSLVIKLKDDIQNCIEQVQNLH 950
951 CKINSYVKEWQKMEFLWQITEEAFLEVVDNSTQRCFGILKGLLDSQSKFD 1000
1001 LIISRNNFSKNLVLHTEDAQRHIRSKMDSWILYVSKHLLTIYERDARKLH 1050
1051 EDMNRDREAVEDMDINFTSLKNITVIIEAVNVNKRHLTERDIQIKLLGSV 1100
1101 MRALTKLKVRFPSHFVYIDQLDNDFSSLRQSLSYVEQELQKHRVVIAKSL 1150
1151 EEGVENINNLSQSLNESWSVRKPISPTLTPPEALKILEFFNESITKLKKK 1200
1201 MHSVAAAAKMLLIPVVLNDQLTHVVEEVKTYDLVWRSIKNLWEDVQRTFE 1250
1251 TPWCRVDVLLLQSDLANFLRRADELPRAVKQFEMYKSLFSQVNMLTSVNK 1300
1301 ILVELKDGALKPRHWNMIFRDIGKRQIQKNLLDKLEFSLKDVMVLNLTLN 1350
1351 EILLTKIIERAQKEFVIEKSLNRIKKFWKEAQYEVIEHSSGLKLVREWDV 1400
1401 LEQACKEDLEELVSMKASNYYKIFEQDCLDLESKLTKLSEIQVNWVEVQF 1450
1451 YWLDLYGILGENLDIQNFLPLETSKFKSLTSEYKMITTRAFQLDTTIEVI 1500
1501 HIPNFDTTLKLTIDSLKMIKSSLSTFLERQRRQFPRFYFLGNDDLLKIIG 1550
1551 SGKHHDQVSKFMKKMFGSIESIIFLEDFITGVRSVEGEVLNLNEKIELKD 1600
1601 SIQAQEWLNILDTEIKLSVFTQFRDCLGQLKDGTDIEVVVSKYIFQAILL 1650
1651 SAQVMWTELVEKCLQTNQFSKYWKEVDMKIKGLLDKLNKSSDNVKKKIEA 1700
1701 LLVEYLHFNNVIGQLKNCSTKEEARLLWAKVQKFYQKNDTLDDLNSVFIS 1750
1751 QSGYLLQYKFEYIGIPERLIYTPLLLIGFATLTDSLHQKYGGCFFGPAGT 1800
1801 GKTETVKAFGQNLGRVVVVFNCDDSFDYQVLSRLLVGITQIGAWGCFDEF 1850
1851 NRLDEKVLSAVSANIQQIQNGLQVGKSHITLLEEETPLSPHTAVFITLNP 1900
1901 GYNGRSELPENLKKSFREFSMKSPQSGTIAEMILQIMGFEDSKSLASKIV 1950
1951 HFLELLSSKCSSMNHYHFGLRTLKGVLRNCSPLISEFGEGEKTVVESLKR 2000
2001 VILPSLGDTDELVFKDELSKIFDSAGTPLNSKAIVQCLKDAGQRSGFSMS 2050
2051 EEFLKKCMQFYYMQKTQQALILVGKAGCGKTATWKTVIDAMAIFDGHANV 2100
2101 VYVIDTKVLTKESLYGSMLKATLEWRDGLFTSILRRVNDDITGTFKNSRI 2150
2151 WVVFDSDLDPEYVEAMNSVLDDNKILTLPNGERLPIPPNFRILFETDNLD 2200
2201 HTTPATITRCGLLWFSTDVCSISSKIDHLLNKSYEALDNKLSMFELDKLK 2250
2251 DLISDSFDMASLTNIFTCSNDLVHILGVRTFNKLETAVQLAVHLISSYRQ 2300
2301 WFQNLDDKSLKDVITLLIKRSLLYALAGDSTGESQRAFIQTINTYFGHDS 2350
2351 QELSDYSTIVIANDKLSFSSFCSEIPSVSLEAHEVMRPDIVIPTIDTIKH 2400
2401 EKIFYDLLNSKRGIILCGPPGSGKTMIMNNALRNSSLYDVVGINFSKDTT 2450
2451 TEHILSALHRHTNYVTTSKGLTLLPKSDIKNLVLFCDEINLPKLDKYGSQ 2500
2501 NVVLFLRQLMEKQGFWKTPENKWVTIERIHIVGACNPPTDPGRIPMSERF 2550
2551 TRHAAILYLGYPSGKSLSQIYEIYYKAIFKLVPEFRSYTEPFARASVHLY 2600
2601 NECKARYSTGLQSHYLFSPRELTRLVRGVYTAINTGPRQTLRSLIRLWAY 2650
2651 EAWRIFADRLVGVKEKNSFEQLLYETVDKYLPNQDLGNISSTSLLFSGLL 2700
2701 SLDFKEVNKTDLVNFIEERFKTFCDEELEVPMVIHESMVDHILRIDRALK 2750
2751 QVQGHMMLIGASRTGKTILTRFVAWLNGLKIVQPKIHRHSNLSDFDMILK 2800
2801 KAISDCSLKESRTCLIIDESNILETAFLERMNTLLANADIPDLFQGEEYD 2850
2851 KLLNNLRNKTRSLGLLLDTEQELYDWFVGEIAKNLHVVFTICDPTNNKSS 2900
2901 AMISSPALFNRCIINWMGDWDTKTMSQVANNMVDVIPMEFTDFIVPEVNK 2950
2951 ELVFTEPIQTIRDAVVNILIHFDRNFYQKMKVGVNPRSPGYFIDGLRALV 3000
3001 KLVTAKYQDLQENQRFVNVGLEKLNESVLKVNELNKTLSKKSTELTEKEK 3050
3051 EARSTLDKMLMEQNESERKQEATEEIKKILKVQEEDIRKRKEVVMKSIQD 3100
3101 IEPTILEAQRGVKNIKKQQLTEIRSMVNPPSGVKIVMEAVCAILGYQFSN 3150
3151 WRDIQQFIRKDDFIHNIVHYDTTLHMKPQIRKYMEEEFLSDPNFTYETIN 3200
3201 RASKACGPLYQWVNAQINFSKVLENVDPLRQEMKRIEFESLKTKANLLAA 3250
3251 EEMTQDLEASIEVSKRKYSLLIRDVEAIKTEMSNVQANLDRSISLVKSLT 3300
3301 FEKERWLNTTKQFSKTSQELIGNCIISSIYETYFGHLNERERADMLVILK 3350
3351 RLLGKFAVKYDVNYRFIDYLVTLDEKMKWLECGLDKNDYFLENMSIVMNS 3400
3401 QDAVPFLLDPSSHMITVISNYYGNKTVLLSFLEEGFVKRLENAIRFGSVV 3450
3451 IIQDGEFFDPIISRLISREFNHAGNRVTVEIGDHEVDVSGDFKLFIHSCD 3500
3501 PSGDIPIFLRSRVRLVHFVTNKESIETRIFDITLTEENAEMQRKREDLIK 3550
3551 LNTEYKLKLKNLEKRLLEELNNSQGNMLENDELMVTLNNLKKEAMNIEKK 3600
3601 LSESEEFFPQFDNLVEEYSIIGKHSVKIFSMLEKFGQFHWFYGISIGQFL 3650
3651 SCFKRVFIKKSRETRAARTRVDEILWLLYQEVYCQFSTALDKKFKMIMAM 3700
3701 TMFCLYKFDIESEQYKEAVLTMIGVLSESSDGVPKLTVDTNNDLRYLWDY 3750
3751 VTTKSYISALNWFKNEFFVDEWNIADVVANSENNYFTMASERDVDGTFKL 3800
3801 IELAKASKESLKIIPLGSIENLNYAQEEISKSKIEGGWILLQNIQMSLSW 3850
3851 VKTYLHKHVEETKAAEEHEKFKMFMTCHLTGDKLPAPLLQRTDRFVYEDI 3900
3901 PGILDTVKDLWGSQFFTGKISGVWSVYCTFLLSWFHALITARTRLVPHGF 3950
3951 SKKYYFNDCDFQFASVYLENVLATNSTNNIPWAQVRDHIATIVYGGKIDE 4000
4001 EKDLEVVAKLCAHVFCGSDNLQIVPGVRIPQPLLQQSEEEERARLTAILS 4050
4051 NTIEPADSLSSWLQLPRESILNYERLQAKEVASSTEQLLQEM 4092
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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