 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8K4E0 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MEPEDLPWPDELEEEEEEEEEEGEEEEGKKEVENASAAATEEALTSEESG 50
51 RLEEFEEAGPDLDFNYESQRQESSDEEEDELAKAWLQAHPDRPGSAFSLP 100
101 PPTPPPPPPPLSPRLRYTPVEHLGKTEVVPLTCRVWQQSSYQDNSRAQFS 150
151 NSSTMLLETGVRWGSEEDQRTESWHCLPQERDSSQTLAMSQTEIGRVEGT 200
201 EVPDLPSQEGGLPAQSQCPGKKPKLNVLCSPLLVIQDNFAAPDLPLLTCL 250
251 IQDQEEVEPDSLFQQSELEFAPLRGIPDKSEDSEWLARPSEVSEALIQAT 300
301 SETSSDLANSCFSISQHPLTEGLQGKAESGVLTRCGDAKYSSLYENLGAQ 350
351 SERIAVLQREVGCSNLGISQASPSSLPSFVPQEPTSEPEYHSSNLRMLRV 400
401 SPDTLLTTHTHSAGSADQKIGAAVVSSAYSQEIKPGSFHQEELPDRHLNE 450
451 EIRKVSPALRTAGQKPEMLPVQSSSYSKGMKSIFYQHPVSHGHQGKEPLS 500
501 VSAVCGSAGNKAFHQLSTLSDSLLTEETWPVSVIPGLGNQKTPLPSEFSL 550
551 SYSHRGKNLPEDVVKVSTDSGSAHKKADILTASSRTYQHKMKPANIYHQE 600
601 LPDSRVPIGTRKVAFESGPAGQKSGVSHPYGEMPSVFYQQGLPDRHSAKS 650
651 PTKTFIPGPADQKTDLSPVPPTSSSHAEKPVSPYQLTLPGSHLPEDVFKA 700
701 SSVCKSSDELSGITALTSASYSYKGRPNSSYQQKFPDSHLNEEAQKILGT 750
751 TGTVDQKTVTPTMSSSFLQKEKPSIFYQQTLPDGGLSEEDLQVSAVPWPA 800
801 DQNIAIPTVTSAAFSQREKPRIFYQQTLSVDRLPGEPLNVLGTSGPPDQN 850
851 TGAPTVTPSSYFPGEESIIFYQAGFPGNTLSAMSFKVPRISGSTEQTNVT 900
901 TGSSSSYSVGEKSIIFYHQALPDGRLPQEASPAPADLNTGEPPMYLASCS 950
951 VGVKPIIFYQQPMSDSQRTKGHKESDVPGPTDQKTGIATVHSTSQSYIGR 1000
1001 RTVSYQKEFPDLSEKALKVLGDVGSTEQKTQIPVVSSALLHKEGPSAYQE 1050
1051 DLPDLTEEPLQILGVSEEVSSSSYQRKLPDHIEVFLKSVGSGSADRKTGA 1100
1101 QIVSSSREKSSGFHQQELPNTGGDAVDAFHPEPVVQEVRKVQTPGAPAGP 1150
1151 SSSHFHKEKLSDYQKASPHRDLTESSLKASTVPGLSDQKKKPAVSSGFCL 1200
1201 HKEKHEISASALLNCQTAELLTVTQRSCLHREDPAISTVIKPDDQKIPLP 1250
1251 TTFHGSSDQKVKPVIFVQKQLRDRDQSEDIPKISTVSEPTVVNTVLPVLL 1300
1301 PGSYSHREKSDSFYPQELPDGHLTEVDLKVSSGLGQADQISGLPTGIPGT 1350
1351 YSHSEKHQLISEHVQELMDNLNSSESSCLSVDSMPLNSQIDDGVIICKPE 1400
1401 SLGFANAGCEEMQNIDRGSKTLKEIQTLLMEAENMALKRCNFSVPLVPFR 1450
1451 DVNDVSFIRSKKVVCFKESSTTDVCTQRESFVEEVPHIEYVQKDIGTQTN 1500
1501 LKYQRGVGNWEFISSATFRSPLQEAEGTARMAYDETFRQYKAARSVMRSE 1550
1551 PEGCSTGIGNKMIIPMMTIIKSDSSSDVSDGCCSWDNNLPESLESVSDVF 1600
1601 LNFFPYTSPKTSITDSREEEWLSESEDGYGSTDSLAAHVKYLLQCETSLN 1650
1651 QAKQILKNAEEEEYRVRTQAWNLKFNLGRDRGYSISELNEDDRRKVEEIK 1700
1701 AKLFGHGRATHMSEGLRSPQGIGCLPEAVCSRIIIESHEKGCFRTLTAEQ 1750
1751 PRPDSCHCAFRSVEPSDLIRGHRSPSSWRGRHINLSRSIEQSNPCFKVGS 1800
1801 SFQLQSHPPFQKLLPDDIKISKGVGMPVHAYMDPQPSELVEPTCVPAKEM 1850
1851 DFPSSSQILPPEPKKQFTTAITFSSHEHSECISDSSGCKVGVTADSQCSG 1900
1901 PSLGVFKPHIPEEQISPRDLKQKTSFQSSLERHGSTPVTILADGSRQRQK 1950
1951 LPVDFEHSHQKEKLLQRLGFKVSHSEPNVSTNVSNFKGVQFSGKDTIVSQ 2000
2001 DKLTSTVEVKEKNVTVTPDLPSCIFLEQPELFEESHTPHTDLQMRKYPSP 2050
2051 SCPEIASRIFLEQPKLSEQSKAPHVDREIREDHSFFPKCQDYIVADPSPD 2100
2101 FPDQQQCKPPDVVGHTRKQNSLLSEGQDYELEEVQHIPQSYFSNMVNVEA 2150
2151 KVSDAISQSAPDHCTAASTPPSNRKALSCVRITLCPKTSSKLDSGTLGER 2200
2201 FHSLDPASKTRINSEFNSDLRIISSRSLEPTSKLLTCKPVAQDQESLVFL 2250
2251 GPKSPLDLQVAQSSLPDSKTIFQDLKTKPPQNSQIVTSRQTQVNISHLEG 2300
2301 YSKPEGTPVSADGSQEQSKVSFTTSFGKLSSDAITQITTESPEKTTFSSE 2350
2351 IFIHADDRGQGILDPMAQKPSRFASSSSVQQIPASHGKDAQPVLLPYKPS 2400
2401 GSSKMYYVPLLKRVPSYLDSKSDTTVESSHSGSNDAIAPDFPPQMLGTRD 2450
2451 DDLSNTVNIKHKEGIYSKRAATKGKNPSQKGDAAAPVQMPITWDENVLDE 2500
2501 NQEEVISRGVVIKMAGPEEMSSLEKDLAGPSDITVQDRKTENLPDTKSIK 2550
2551 QKEGSLEIESECHSAFENTAHSVFRSAKFYFHHPVHLPHEQDFCHESLGR 2600
2601 SVFMQHSWKDFFHHHSGHSCLPPPGPSSDKLDKTKMDYTRIKSLSINLNL 2650
2651 GEHEKIHTIKNQARDPKGKRQANEQKKDQKVTPELTTECPVSLNELWNRY 2700
2701 QERQKQQNPSGACDTKELSLVERLDRLAKLLQNPITHSLRASESAQDDSR 2750
2751 GGHRAREWTGRRQQKQKGKQHRKWSKSLERGQSTGDFRKSKVFSPHQGGK 2800
2801 SSQFKIEQIKLDKYILRKEPGFNNVSNTSLDSRPSEESVSLTDSPNIFSS 2850
2851 TDSPVDSDVLTPTDRDMPLNERSSSISTIDTVRLIQAFGQDRLSLSPRRI 2900
2901 KLYSTVTSQRRRYLEQPCKHNRKALNTACPQMTSEHSRRRHIQVANHMTS 2950
2951 SDSVSSPGSLLSLDSALSNEETVRMVSKGVQAGNLEIVAGVKKYTQDVGV 3000
3001 TFPTPSSSEARLEEDSDVTSSSEEKAKEKKFLSNYLQTKNLRKNKPNPCA 3050
3051 GVSWFVPVESGQSGSKKENLPKIYRPVISWFEPVTKTKPWREPLREQNWQ 3100
3101 AQCMNSRGSLGGPGRDSGQVSLRPFVRATLQESLQLHRPDFISHSGERIK 3150
3151 RLKLLVQERKLQSLFQSEREALFHSARPLPRRVLLAVQKNKPIGKKEMIQ 3200
3201 RTRRIYEQLPEVKKKREEEKRKSEYKSYWLRAQHYKMKVTNHLLGRKVPW 3250
3251 D 3251
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.