 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8BLN6 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MVKRKSSEGQEQDGGRGIPLPIQTFLWRQTSAFLRPKLGKQYEASCVSFE 50
51 RVLVENKLHGLSPALSEAIQSISRWELVQAALPHVLHCTATLLSNRNKLG 100
101 HQDKLGVAETKLLHTLHWMLLEAPQDCNNDQFGGTDRGSSWGGSSSAFIH 150
151 QIENQGSPGQPCRSSSHDEEENNRRKTFQNSMATVELFVFLFAPLVHRIK 200
201 ESDLTFRLASGLVIWQPMWEHRQPEVSGFTALVKPIRNIITAKRSSPINS 250
251 QSQTCESPNQDTRQQGEGLQVVSEALQSDSISPKATISGCHQGNSFDGSL 300
301 SSQTSQERGPSHSRASLVIPPCQRSRYATYFDVAVLRCLLQPHWSEEGTQ 350
351 WSLMYYLQRLRHMLEEKPEKTPDPDIPLLPRPRSSSMVAAAPSLVNTHKT 400
401 QDLTMKCNEEEKSLSPEAFSKVSLTNLRRSAVPDLSSDLGMNIFKKFKSR 450
451 KEDRERKGSIPFHHTGKRRPRRMGVPFLLHEDHLDVSPTRSTFSFGSFSG 500
501 LGEDRRGIEKGGWQTTILGKLTRRGSSDAATEMESLSARHSHSHHTLVSD 550
551 LPDHSNSHGENTVKEVRSQISTITVATFNTTLASFNVGYADFFSEHMRKL 600
601 CSQVPIPEMPHEPLACANLPRSLTDSCINYSYLEDTEHIDGTNNFVHKNG 650
651 MLDLSVVLKAVYLVLNHDISSRICDVALNIVECLLQLGVVPCVEKNRKKS 700
701 ENKENESVEKRPSEGAFQFKGVSSSSTSGFGAPSASGAGDGGGEEGGGGD 750
751 GGGGGGGGDGGGGGGGGGGPYEKNEKNQEKDDNIPVSNHRLALTMLIKIV 800
801 KSLGCAYGCGEGHRGLSGDRLRHQVFRENAQNCLTKLYKLDKIQFRQTMR 850
851 DYVNKDSLNNVVDFLHALLGFCMEPVTDNKAGFGNNFTTVDNKSTAQNVE 900
901 GIIVGAMFKSLITRCASTTHELHSPENLGLYCDIRQLVQFIKEAHGNVFR 950
951 RVALSALLDSAEKLAPGKKVEENGQESKPVGSKRSEAGSIADKGQVSSAP 1000
1001 EECRSFMSGRPSQTPEHDEPMQGGNLGRKDFWRKMFKSQSAASDTSSQSE 1050
1051 QDTSECTTAHSGNTSDRRARSRSRRISLRKKLKLPIGNWLKRSSLSGLAD 1100
1101 GVEDLLDISSVDRLSFIRQSSKVKFTSAVKLSEGGPGSGMENGREEEENF 1150
1151 FKRLGCHSFDDHLSPNQDGGKSKNVVNLGAIRQGMKRFQFLLNCCEPGTI 1200
1201 PDASILAAALDLEAPVVARAALFLECARFVHRCNRGNWPEWMKGHHVNIT 1250
1251 KKGLSRGRSPTVGNKRNQKLQWSAAKLFYQWGDAIGIRLNELCHGESESP 1300
1301 ANLLGLIYDEETKRRLRKEDEEEDFLDDSTVNPSKCGCPFALKMAACQLL 1350
1351 LEITTFLRETFSCLPRPRTEPLVDLESCRLRLDPELDRHRYERKISFAGV 1400
1401 LDENEDSKDSLHSSSHTIKSDAGAEEKKVPSRKIRIGGSRLLQIKGTRSF 1450
1451 QVKKGGSLSSIRRVGSLKSSKLSRQDSESEAEELQLSQSRDTVTDLEGSP 1500
1501 WSASEPSIEPEGLSNAGTEENYHRNMSWLHVMILLCNQQSFICTHVDYCH 1550
1551 PHCYLHHSRSCARLVRAIKLLYGDSVDSLRESNHISNVALRGKKQKECSD 1600
1601 KSCLRTPSLKKRVSDVNLEGKKDSGMLKYIRFQVMSLSPAPLSLLIKAAP 1650
1651 ILTEEMYGDIQPAAWELLLSMDEHMAGAAAAMFLLCAVKVPDAVSDMLMS 1700
1701 EFHHAETVQRLNAVLKFHTLWRFRYQVWPRMEEGAQQIFKIPPPSINFTL 1750
1751 PSPVLGMPSVPMFDPPWVPQCSGSVQDPINEDQSKSFSARAVSRSHQRAE 1800
1801 HILKNLQQEEEKKRLGREASLITAIPITQEACYEPTCTPNSEPEEEEEVA 1850
1851 NLTSRRLSVSPSCTSSTSHRNYSFRRGSVWSVRSAVSAEDEEHATEHTPN 1900
1901 HHVPQPPQAVFPACICAAVLPIVHLMEDGEVREDGVAVSAVAQQVLWNCL 1950
1951 IEDPSTVLRHFLEKLTISNRQDELMYMLRKLLLNIGDFPAQTSHILFNYL 2000
2001 VGLIMYFVRTPCEWGMDAISATLTFLWEVVGYVEGLFFKDLKQTMKKEQC 2050
2051 EVKLLVTASMPGTKTLVVHGQNECDIPTQLPVHEDTQFEALLKECLEFFN 2100
2101 IPESQSTHYFLMDKRWNLIHYNKTYVRDIYPFRRSVSPQLNLVHMHPEKG 2150
2151 QELIQKQVFTRKLEEVGRVLFLISLTQKIPTAHKQSHVSMLQEDLLRLPS 2200
2201 FPRSAIDAEFSLFSDPQAGKELFGLDTLQKSLWIQLLEEMFLGMPSEFPW 2250
2251 GDEIMLFLNVFNGALILHPEDSALLRQYAATVINTAVHFNHLFSLSGYQW 2300
2301 ILPTMLQVYSDYESNPQLRRAIEFACHQFYILHRKPFVLQLFASVAPLLE 2350
2351 FPDAANTGSSKGVSAQCLFDLLQSLEGETTDILDILELVKAEKPLKSLDF 2400
2401 CYGNEDLTFSISEAIKLCVTVVAYAPESFRSLQMLMVLEALVPCYLQKMK 2450
2451 RQTSQVETVPAAREEIAATAALATSLQALLYSVEVLTRPMTAPQMSRSDQ 2500
2501 GHKGTTTANHTMSSGVNTRYPEQGAKLHFIRENLHLLEEGQGLPREELDE 2550
2551 RISREEFRRPRESLLNICTEFYKHCGPRLKILQNLAGEPRVTALELLDVK 2600
2601 SHMRLAEIAHSLLKLAPYDTQTMESRGLRRYIMEMLPITDWSAEAVRPAL 2650
2651 ILILKRLDRMFNKIHKMPTLRRQVEWEPASSLIEGVCLTLQRQPIISFLP 2700
2701 HLRSLINVCVNLVMGVVGPSSVADGLPLLHLSPYLSPPLPFSTAVVRLVA 2750
2751 LQIQALKEDFPLSHVISPFTNQERREGMLLNLLIPFVLTVGSGSKDSPWL 2800
2801 EQPEVQLLLQTVINVLLPPRIISTSRSKNFMLESSPAHCSTPGDAGKDLR 2850
2851 KEGLAESTSQAAYLALKVILVCFERQLGSQWYWLSLQVKEMALRKVGGLA 2900
2901 LWDFLDFIVRTRIPIFVLLRPFIQCKLLAQPAENHEELSARQHISDQLER 2950
2951 RFIPRPLCKSSLIAEFNSELKILKEAVHSGSAYQGKTSISTVGTSTSAYR 3000
3001 LSLATMSRSNTGTGTVWEQDSEPSQQASQDTLSRTDEEDEENDSVSMPSV 3050
3051 VSEQEACLLSTIGRRRFSSHVSSMSAPQAEVGMLPSQSEPNVLDDSQGLA 3100
3101 AEGSLSRVASIQSEPGQQNVLLQQPLGRKRGLRQLRRPLLSRQKTQTEPR 3150
3151 NRHGARLSTTRRSIQPKTKPSVDQKRSVTFIEAQPEPTAAPTDIFPATGQ 3200
3201 PQSCSPGRARKPEGTEKPVLTSSPAIIIADLHSLSPKQSEPLLAEEGEKK 3250
3251 EDEEIQGATAHCPLSTQLSDPDDFTGLETSSLLQHGDTVLHISEENGTEN 3300
3301 PLLSSQFTFTPPELGDTDSALDESHV 3326
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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